University College London
TITLE | Smart Cities – Sensing, Emotions and Augmented/Virtual Reality of Urban Space
ABSTRACT | Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few (IBM, 2013). This data can, compared to traditional data sources, be defined as ‘big’. Cities and urban environments are the main sources for big data, every minute 100,000 tweets are sent globally, Google receives 2,000,000 search requests and users share 684,478 pieces of content on Facebook (Mashable, 2012). An increasingly amount of this data stream is geolocated, from Check-ins via Foursquare through to Tweets and searches via Google Now, the data cities and individuals emit can be collected and viewed to make the data city visible, aiding our understanding of now only how urban systems operate but opening up the possibility of a real-time view of the city at large (Hudson-Smith, 2013). The talk explores systems such as The City Dashboard (http://www.citydashboard.org) and the rise of the Internet of Things (IoT) in terms of data collection, visualization and analysis. Joining these up creates a move towards the Smart City and via innovations in IoT a look towards augmented reality pointing towards the the creation of a ‘Smart Citizen’ ‘the Quantified Self’ and ultimately a Smart City.
- IBM (2013), Big Data at the Speed of Business
- Mashable (2012), How Much Data is Created Every Minute
- Hudson-Smith (2013) – Tagging and Tracking, Architectural Design, 01, 2014, High Definition, Zero Tolerance in Design and Production
BIOGRAPHY | Dr Andrew Hudson-Smith is Director of the Bartlett Centre for Advanced Spatial Analysis (CASA) at The Bartlett, University College London. Andy is a Reader in Digital Urban Systems and Editor-in-Chief of Future Internet Journal. He is also an elected Fellow of the Royal Society of Arts, a member of the Greater London Authority Smart London Board and Course Founder of the MRes in Advanced Spatial Analysis and Visualisation and MSc in Smart Cities at University College London. Andy is also a member of the Parliamentary Group on Smart Cities.
TITLE | Geolocated Online Datasets and the Study of Human Behavior
ABSTRACT | The growing diffusion of GPS enabled cell phones coupled with the widespread adoption of social networking tools is opening up new avenues for the study of human behavior. Using a large dataset of geolocated Tweets we present an analysis of both at the temporal and spatial aspects of human communication and interaction. By coupling the analysis of geocoded tweets over a period of two years with tools for automatic language detection we are able to present a large scale study of the geography of language use around the world at scales ranging from country to neighborhood level and how it varies over the course of a year due to seasonal variations of tourism. Finally, we show how the volume of information available in online systems permits the real time gathering of quantitative indicators anticipating the future unfolding of opinion formation events.
BIOGRAPHY | Bruno Gonçalves is a faculty member at Aix-Marseille Université with a strong expertise in using large scale datasets for the analysis of human behaviour. After completing his joint PhD in Physics, MSc in C.S. at Emory University in Atlanta, GA in 2008 he joined the Center for Complex Networks and Systems Research at Indiana University as a Research Associate. From September 2011 until August 2012 he was an Associate Research Scientist at the Laboratory for the Modeling of Biological and Technical Systems at Northeastern University. Since 2009 he has been pursuing the use of Data Science and Machine Learning to study human behavior. By processing and analyzing large datasets from Twitter, Wikipedia, web access logs, and Yahoo! Meme he studied how we can observe both large scale and individual human behavior in an obtrusive and widespread manner. The main applications have been to the study of Information Diffusion, Behavioral Change and Epidemic Spreading. He is the author of over 40 publications and the editor of the forthcoming book Social Phenomena: From Data To Models (Springer, 2014).
University of Cambridge
TITLE | The architecture of innovation: Tracking face-to-face interactions with ubicomp technologies
ABSTRACT | The layouts of the buildings we live in shape our everyday lives. In office environments, building spaces affect employees’ communication, which is crucial for productivity and innovation. However, accurate measurement of how spatial layouts affect interactions is a major challenge and traditional techniques may not give an objective view. We measure the impact of building spaces on social interactions using wearable sensing devices. I will first describe work where we study a single organization that moved between two different buildings, affording a unique opportunity to examine how space alone can affect interactions. Then I will illustrate a study of cultural differences in inter building interaction. The analysis is based on deployments of wireless sensing technologies: short-range, lightweight RFID tags capable of detecting face-to-face interactions. The talk is based on works published at ACM CSCW 2014 and ACM Ubicomp 2014.
BIOGRAPHY | Dr. Cecilia Mascolo is a Reader in Mobile Systems in the Computer Laboratory, University of Cambridge. She held an EPSRC Advanced Research Fellowship from 2005 to 2010 and spent from 2001 to 2007 as an academic in University College London. She has published extensively in the areas of mobile computing, mobility and social modeling and sensor networking and she is a member of programme committees in the areas of ubiquitous and sensor networks as well as social and complex networks. She currently teaches a mobile and sensor systems course as well as a master course on Social and Technological Networks. More details of her profile are available at http://www.cl.cam.ac.uk/users/cm542.
University of Warwick
Wednesday 11th June 2014, 2:35pm
TWITTER | @chestercurme
TITLE | Quantifying the semantics of search behavior before stock market moves
ABSTRACT | The Internet has become a central source of information for many people when making day-to-day decisions. Internet search data, such as from Google Trends, offer the intriguing possibility of measuring the information-gathering processes that precede real-world events. We present a method to mine the vast data Internet users create when searching for information online, in order to identify topics of interest before stock market moves. Crucially, we highlight the utility of categorizing keywords into semantic groups when analyzing these search data. In an analysis of historic data from 2004 until 2012, we find evidence of links between Internet searches relating to politics or finance and subsequent stock market moves. In particular, we find that an increase in search volume for these topics tends to precede stock market falls. We suggest that extensions of these analyses could offer insight into large scale information flow before a range of real-world events.
BIOGRAPHY | Chester Curme is a Ph.D. candidate in the physics department at Boston University, and is currently a research fellow in data science at Warwick Business School. He received his B.A. in physics and mathematics from Middlebury College in 2012, where he graduated with Highest Honors. His research interests lie in interdisciplinary applications of statistical physics to problems in economics, computational social science, and network science. His work has been featured in both TV appearances and articles throughout the worldwide press, including the Financial Times, Washington Post, Wired, Daily Mail, Welt Am Sonntag, El País, Neue Zürcher Zeitung and Forbes. He has reviewed for the journals PLOS ONE and Physica A.
University College London
Thursday 12th June 2014, 2:50pm
TWITTER | @ianalis
TITLE | Dynamics of Conversational Utterances
ABSTRACT | Conversations transfer short bits of information and the speech in each turn is called an utterance. Using conversations in works of fiction and in the online social medium Twitter, we found that the utterance length of conversations is getting shorter with time but adapts more strongly to the constraints of the communication medium. Regional variations of utterance lengths in the US suggest that the lengths are not directly influenced by location but by a demographic variable. Similar results were also found for the UK and Italy, which contradicts the popular notion that there is a North-South divide with respect to talkativeness in these countries. Although not definitive, our use of novel sources of conversations has given us a tantalising look into the dynamics of human conversations.
BIOGRAPHY | Christian Alis is a Research Associate in Data Science at UCL working on the EPSRC project, “Big Data, Innovations and New Business Models”. He received his PhD in Physics for his work on the dynamics of conversational utterances. His discovery that tweets are getting shorter has been covered by online media including MIT Tech Review and Time Magazine.
University College London
Friday 13th June 2014, 11:50am
TWITTER | @danielebarch
TITLE | Quantifying mobility using Flickr data
ABSTRACT | Flickr is one of the world’s largest photo sharing websites, with a reported 92 million users who share more than 1 million pictures per day. A growing number of users upload their pictures using smartphones or other GPS-enabled devices that automatically assign to each photo a time-stamp and a pair of geographical coordinates indicating where and when the image has been taken. The resulting geographical time series that describe people’s trajectories in time and space are a rich source of information that can be used to infer patterns of human mobility and behaviour.
My current research focuses on quantifying bilateral migration patterns between countries using Flickr users’ trajectories. I will also present preliminary results aimed at investigating mobility on a smaller spatial scale: by extending work on the statistical distribution of individuals’ movements, I plan to model underlying contexts that cause the emergence of such mobility patterns.
BIOGRAPHY | Daniele Barchiesi obtained a MSc by research and a PhD from the Centre for Digital Music at Queen Mary University of London, where he has worked on research in the areas of audio engineering, machine learning, signal processing and reproducible research. He joined University College London in January 2014 as a research associate with the project “Big Data, Innovations and New Business Models”, where he is working on analysing social networks and web platforms to model and predict phenomena of social and economic interest. Dr Barchiesi is also a co-founder of Eulergy – the research matchmaker, a startup that aims to connect researchers with SMEs and corporate organisations.
TITLE | Urban*: Crowdsourcing for the good of London
ABSTRACT | For the last two years or so, we have been working on studying social media in the context of London. By combining what Twitter users in a variety of London neighborhoods talk about with census data, we showed that certain topics are correlated (positively and negatively) with neighborhood deprivation. Users in more deprived neighborhoods tweet about wedding parties, matters expressed in Spanish/Portuguese, and celebrity gossips. By contrast, those in less deprived neighborhoods tweet about vacations, professional use of social media, environmental issues, sports, and health issues. More recently, we launched two crowdsourcing websites. First, we launched urbanopticon.org, which extracts Londoners’ mental images of the city. By testing which places are remarkable and unmistakable and which places represent faceless sprawl, we are able to draw the recognizability map of London [1,2]. The site has attracted tens of thousands of players, and I will show you the results published in WWW last year. The second site is called urbangems.org. This crowdsources visual perceptions of quiet, beauty and happiness across the city using Google Street View pictures. The aim is to identify the visual cues that are generally associated with concepts difficult to define such beauty, happiness, quietness, or even deprivation [3,4]. The site has been awarded the A.T. Kearney Prize and has been featured in falling-walls.com 2012 in Berlin.
BIOGRAPHY | Daniele Quercia is a social media researcher at Yahoo Labs in Barcelona. Before that, he was a Horizon senior researcher at The Computer Laboratory of the University of Cambridge. He is interested in the relationship between online and offline worlds and his work has been focusing in the areas of data mining, computational social science, and urban informatics. His research has been published in leading venues including ICSE, Ubicomp, ICDM, CSCW, RecSys, WSDM, and WWW, received honorable mentions from AAAI ICWSM, and has been featured on La Repubblica, The Independent, New Scientist, Le Monde, and BBC. He spoke at TEDx Barcelona and Falling Walls Berlin, and wrote for BBC. He was Postdoctoral Associate at the Massachusetts Institute of Technology where he worked on social networks in a city context, and his PhD thesis at UC London was nominated for BCS Best British PhD dissertation in Computer Science. During his PhD, he was a Microsoft Research PhD Scholar and MBA Technology Fellow of London Business School, and he also interned at the National Research Council in Barcelona and at National Institute of Informatics in Tokyo. He studied at Politecnico di Torino (Italy), Karlsruhe Institute of Technology (Germany), and University of Illinois (USA).
University of Oxford
TITLE | Social Machines and Social Media
ABSTRACT | Tim Berners-Lee wrote “Real life is and must be full of all kinds of social constraint – the very processes from which society arises. Computers can help if we use them to create abstract social machines on the Web: processes in which the people do the creative work and the machine does the administration… The stage is set for an evolutionary growth of new social engines. The ability to create new forms of social process would be given to the world at large, and development would be rapid.” This talk presents the Social Machines perspective and considers Social Media not just as a lens onto social behaviour but a means of empowering the creation of new social processes.
BIOGRAPHY | David De Roure is Director of the e-Research Centre at University of Oxford and Professor of e-Research. Focused on multidisciplinary digital research, he has worked closely with Social Sciences and Digital Humanities as well as science fields including physics and bioinformatics, pursuing innovation in digital scholarship and developing new forms of scholarly communication in the context of methodological change. His personal research is in Web Science, especially “social machines”, and in computational musicology. He is a Strategic Adviser to ESRC in the area of Social Media data.
University College London
TITLE | Investigating the Role of Cognitive Biases in Urban Route Choice
ABSTRACT | Route choice is typically assumed to be an optimisation process, where individuals minimise their distance or time costs while travelling between origin and destination. However, evidence from behavioural and neurological studies suggest that human navigation is considerably more complex process, influenced by cognition of space and variation in perception and preference. In this work, a large collection of minicab GPS route traces is examined in detail, with a range of approaches applied towards more comprehensively understanding route choice behaviour in urban areas. The analyses demonstrate the shortcomings of assumed optimisation on the part of the decision-maker, highlighting the role of heterogeneity in urban space and individual preference. In view of the findings, a behavioural framework is introduced as a possible way forward for the future modelling of route choice in urban areas.
BIOGRAPHY | Dr Ed Manley is a Research Associate at the UCL Centre for Advanced Spatial Analysis (CASA). His research involves the utilisation of large datasets in order to improve the understanding of social processes in urban areas. In his current research, he is examining the use of Oyster Card data for the analysis, prediction and mitigation of disruption on the London Underground.
University of Warwick
TITLE | Counting crowds with mobile phone and Twitter data
ABSTRACT | A large dataset of mobile phone network access records and geo-localized tweets in Milan, Italy, was released at the start of 2014. Here, we present results showing how we can infer the number of people attending events in restricted spaces, such as football games, by making use of the information contained in these two datasets.
BIOGRAPHY | Federico Botta is a PhD student in the Centre for Complexity Science at the University of Warwick. After a BSc degree in physics and a first MSc in theoretical physics, both obtained at the Universita’ degli Studi di Milano-Bicocca, Milan, Italy, he moved to Warwick to join the Doctoral Training Centre in Complexity Science. He obtained a second MSc in Complexity Science, awarded with Distinction, and started his PhD in October 2013, after being awarded a full EPSRC scholarship.
His interests range from the analysis of complex and real-world networks, with a particular focus on the detection and definition of communities, to computational social sciences, with a strong interest on large datasets that explore people’s behaviour. Other areas of research include the study of connections between statistical physics and networks and, more broadly, the mathematical modelling of real-world systems.
University of Oxford
Wednesday 11th June 2014, 1:45pm
TITLE | Using simple social mechanisms to understand collective online behaviour
ABSTRACT | Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviours to population-level outcomes. In my talk I will consider a simple generative model for the collective behaviour of millions of social networking site users who make choices between different software applications that they can install. The proposed model incorporates two distinct social mechanisms: (1) imitative behaviour reflecting the influence of recent installation activities of other users; (2) rich-get-richer popularity dynamics where users are influenced by the cumulative popularity of each application. Interestingly, although various combinations of the two mechanisms yield long-time behaviour that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent installation activities of other users over their cumulative popularity. More generally this demonstrates that even when using purely observational data, as opposed to experimental research designs, temporal data-driven modelling can in fact effectively distinguish between competing microscopic mechanisms, providing novel insights into collective online behaviour
BIOGRAPHY | Felix Reed-Tsochas is the James Martin Lecturer in Complex Systems and Associate Dean of Research at the Saïd Business School, where he also directs the CABDyN Complexity Centre. He leads the Oxford Martin Programme on Complexity, Risk and Resilience at the Oxford Martin School, and together with Doyne Farmer directs the Programme in Complexity Economics that is part of the Institute for New Economic Thinking (INET) at the Oxford Martin School. His research interests, informed by a background in condensed matter physics, broadly focus on the structure and dynamics of complex networks, including social networks, financial networks, ecological networks, and supply networks. One overarching question that integrates many of the research projects that he and his group are working on is how collective behaviours and structures in groups and populations can be related to the decisions and actions of individual agents or actors.
University of Sussex
TITLE | Mappiness: what’s a crowdsourced, geolocated, longitudinal social survey good for?
ABSTRACT | Mappiness pings users’ smartphones twice daily to ask how they’re feeling, and uses satellite positioning to discover their location while they answer. This simple procedure has generated a rich panel (longitudinal) data set, comprising millions of responses from tens of thousands of individuals. Although Mappiness was designed principally to investigate how we’re affected by our immediate environment, it can shed new light on a range of other questions in the social sciences and beyond — including the relationships between our happiness and work, cultural activities, terrorism, weather and football.
BIOGRAPHY | George MacKerron lectures in environmental and behavioural economics at the University of Sussex, with affiliations to UCL and LSE. His research covers topics including subjective wellbeing, environmental quality, spatial analysis and crowdsourcing. George leads the Mappiness study, providing new and unique evidence on how our happiness is linked to our environment. He is also Chief Technical Officer for Psychological Technologies, a startup company developing apps for mindfulness, workplace wellbeing, and more.
Friday 13th June 2014, 9:00am
TITLE | Switching without Switches and the Fragility of Interdependency: Some Applications to Failure Cascades in Economics
ABSTRACT | Recent disasters ranging from abrupt financial “flash crashes” and large-scale power outages to sudden death among the elderly dramatically exemplify the fact that the most dangerous vulnerability is hiding in the many interdependencies among different networks. In the past year, we have quantified failures in interconnected networks, and demonstrated the need to consider mutually dependent network properties in designing resilient systems. Specifically, we have uncovered new laws governing the nature of switching phenomena in coupled networks, and found that phenomena that are continuous “second order” phase transitions in isolated networks become discontinuous abrupt “first order” transitions in interdependent networks. We discuss the network basis for understanding sudden death in the elderly, and the possibility that financial “flash crashes” are not unlike the catastrophic first-order failure incidents occurring in coupled networks .
This work was supported by DTRA, ONR, and NSF, and was carried out in collaboration with a number of students and colleagues, including but not limited to S. V. Buldyrev, S. Havlin, D. Y. Kenett, A. Majdandzic, H. S. Moat, B. Podobnik and T. Preis.
1. A. Majdandzic, B. Podobnik, S. V. Buldyrev, D. Y. Kenett, S. Havlin, and H. E. Stanley, “Spontaneous Recovery in Dynamical Networks,” Nature Physics 10, 34 (2014).
BIOGRAPHY | H. Eugene Stanley is an American physicist and University Professor at Boston University. He has made seminal contributions to statistical physics and is one of the pioneers of interdisciplinary science. His current research focuses on understanding the anomalous behavior of liquid water, but he had made fundamental contributions to complex systems, such as quantifying correlations among the constituents of the Alzheimer brain, and quantifying fluctuations in noncoding and coding DNA sequences, interbeat intervals of the healthy and diseased heart. He is one of the founding fathers of econophysics.
University of Oxford
TITLE | Building Data Science into Policy Design? A Case Study of Petition Signing Data
ABSTRACT | Petition platforms, where citizens may create and sign petitions to the government or legislature, have been adopted in many liberal democracies, including the US, the UK and Germany. These platforms can be mined to generate ‘big data’ on petition signing which provides new insight into the ecology of this form of political participation, data of a kind rarely seen in political science. This paper visualizes and models such data for all petitions created on the UK government petition platform over a three year period (including a comparison with similar data for the US); illustrates the effect on petition signing of a platform change to provide social information in the form of trending petitions; and shows how the analysis of such data might be used to inform policy change and platform redesign.
BIOGRAPHY | Helen Margetts is the Director of the Oxford Internet Institute, Univesity of Oxford and Professor of Society and the Internet. She is a political scientist specialising in digital governance and politics, investigating relationships between governments, citizens and the Internet and related digital technologies in the UK and internationally. She has published major research reports in this area for agencies such as the OECD and the UK National Audit Office, and many articles and books, including Digital Era Governance (OUP, 2006, 2008); the Tools of Government (Macmillan, 2007); and Paradoxes of Modernization (OUP, 2010). She is editor of the journal Policy and Internet. She sits on the Digital Advisory Board of the UK government. She holds the ESRC professorial fellowship ‘The Internet, Political Science and Public policy: Re-examining Collective Action, Governance and Citizen-Governance Interactions in the Digital Era’ (2011-4).
Central European University
Thursday 12th June 2014, 2:10pm
TITLE | Spreading on temporal networks
ABSTRACT | Spreading is one of the most important processes taking place on networks with relevance to epidemiology, computer science and sociology. Investigating Big Data has revealed that the transmission events are usually very inhomogeneously distributed: They are bursty, thus theories based on Poisson processes fail. A careful analysis of the communication events revealed strong, nontrivial dependency between them. We have studied spreading on communication networks and analyzed the different contributions influencing the speed of contagion using appropriate null models. The result is that burstiness and modular structure coupled with the Granovetterian correlations between link weights and topology have decelerating effect on spreading. However, in some other cases acceleration as compared to Poisson processes were observed. In order to get deeper understanding we carried out analytical and numerical model calculations of the susceptibleinfected (SI) model on temporal networks and obtained a complex picture with both acceleration and deceleration, depending on the burstiness, the topology and the nonstationarity of the process.
BIOGRAPHY | János Kertész obtained his PhD in Physics 1980 from Eötvös University. He worked at the Research Institute of Technical Physics of the Hungarian Academy of sciences, at the Cologne University and at Technical University Munich. He has been professor since 1992 at the Budapest University of Technology and Economics, and since 2012 at the Center for Network science of the Central European University. He was visiting scientist in Germany, US, France, Italy and Finland. He is interested in statistical physics and its applications. During the last 15 years his research has focused on multidisciplinary topics, mainly on complex networks as well as on financial analysis and modeling. He has published more than 200 scientific papers. He has been on the editorial boards of Journal of Physics A, Physica A, Fluctuation and Noise Letters, Fractals, New Journal of Physics. His work has been awarded with the Hungarian Academy Award, the SzentGyorgyi Award of the Ministry of Education and Culture, and the Széchenyi Prize.
Charles University in Prague
Thursday 12th June 2014, 4:10pm
TWITTER | @lkristoufek
TITLE | What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis
ABSTRACT | Bitcoin has emerged as a fascinating phenomenon of the financial markets. Without any central authority issuing the currency, it has been associated with controversy ever since its popularity and public interest reached high levels. Here, we contribute to the discussion by examining potential drivers of Bitcoin prices ranging from fundamental to speculative and technical sources as well as a potential influence of the Chinese market. The evolution of the relationships is examined in both time and frequency domains utilizing the continuous wavelets framework so that we comment on development of the interconnections in time but we can also distinguish between short-term and long-term connections.
BIOGRAPHY | Ladislav Kristoufek, Ph.D. is a research associate at the Institute of Information Theory and Automation, Academy Sciences of the Czech Republic, and an assistant professor at the Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Czech Republic. Main research interests are – econophysics, financial econometrics, computational social science, complex systems and statistics.
University of Warwick
Wednesday 11th June 2014, 2:50pm
TITLE | Quantifying the Relationship Between Financial News and the Stock Market
ABSTRACT | The complex behavior of financial markets emerges from decisions made by many traders. Here, we exploit a large corpus of daily print issues of the Financial Times from 2nd January 2007 until 31st December 2012 to quantify the relationship between decisions taken in financial markets and developments in financial news. We find a positive correlation between the daily number of mentions of a company in the Financial Times and the daily transaction volume of a company’s stock both on the day before the news is released, and on the same day as the news is released. Our results provide quantitative support for the suggestion that movements in financial markets and movements in financial news are intrinsically interlinked.
BIOGRAPHY | Merve Alanyali is a Masters student in Complex Systems Science at the University of Warwick. Her research focuses on the analysis of large open data sources with concepts and methods stemming from image processing and machine learning. Merve’s recent findings of a relationship between the number of mentions of a company in the Financial Times and the transaction volume of a company’s stock were the focus of substantial media attention, including a piece in the Financial Times and coverage on Australian television. Merve graduated with high honours in Computer Science from Izmir University of Economics in 2011, and has subsequently studied at universities in the UK, Russia and Sweden. She was recently awarded a Chancellor’s International Scholarship to allow her to begin a PhD in Data Science at Warwick Business School, University of Warwick, in October 2014.
University of the Balearic Islands
TITLE | Is the Voter Model a Model for Voters?
ABSTRACT | Election data provide a framework for contrasting opinion models, a task that has remained elusive. We identify three tasks: determining generic features of election data that should be described by a basic opinion model, identify an appropriate interaction mechanism and a plausible interaction network. We analyze election data of US presidential elections from year 1980 to 2012 and find that the vote-share distribution follows approximately a Gaussian distribution with a constant standard deviation from election to election, although the average value changes. Another feature is the logarithmic decay in vote-share spatial correlations. We develop a social influence opinion model based on random imperfect imitation, i.e., a voter model like interaction with the addition of random noise. As a proxy for the interaction network we use census data on commuting that counts how many individuals live in one county and work in another one. This gives input data fixing the value of the parameters of the model. The agents interact a proportion of their times at their home location with other agents they can meet and otherwise they interact at their working location. The model accounts for the two generic features of election data mentioned above. Furthermore it recovers the behavior of these properties when the geographical space is coarse grained at different scales—from the county level through congressional districts, and up to states. Finally, we analyze the role of the mobility range and the randomness in decision making, which are consistent with the empirical observations.
BIOGRAPHY | Maxi San Miguel is Professor of Physics at the University of the Balearic Islands (since 1986) and Director of IFISC (Institute for Cross-Disciplinary Physics and Complex Systems, CSIC-UIB), Palma de Mallorca, Spain. His research activity spans across different fields of Statistical and Nonlinear Physics (Stochastic Processes, Phase Transitions, Pattern Formation and Spatio-temporal Complexity, Complex Networks) and Computational Social Science, as well as Laser Physics and Photonics. He is the author of over 315 papers quoted over 10.200 times (h index=47). His main current research addresses emergent complex phenomena in collective social phenomena, where he has introduced the co-evolutionary dynamics of networks and agents, and he has contributed to the present understanding of problems of cooperation and social consensus such as opinion formation, cultural dissemination and language competition dynamics. Maxi San Miguel was coordinator for Physics and Mathematics of ANEP (Spanish National Evaluation Agency), chairman of the EPS Division on Statistical and Nonlinear Physics (1998-2002), and he is member of the IUPAP commission on Statistical Physics. He received the Medal of the Spanish Physical Society-Fundación BBVA in 2010.
University College London
TITLE | Exploring City Area to Define Size and Scale
ABSTRACT | In this talk, I will begin with the notion that as cities get bigger, they get more than proportionately richer. This is an old idea in economics and one of its progenitors, Alfred Marshall, at the end of the nineteenth century defined these notions as ‘economies of urban agglomeration’. More recently the group of researchers at Santa Fe, in particular Luis Bettencourt and Geoff West, have argued that within the confines of comparable entities – cities – that define urban systems, as they grow, their income increases at a rate which is more than proportionate to their size, that is ,if their size increases by 100%, their income increases by some 112%. This is positive allometry or superlinear scaling as it is referred to and it has been demonstrated quite categorically for the US urban system comprising some 366 Metropolitan Statistical Areas. However in this talk, I will report the work of our group which has demonstrated equally conclusively that no such positive allometry exists for the UK urban system. Much of our analysis rests on the fact that it is extremely difficulty to define cities categorically with respect to their physical extent over which we need to measure their attributes – population, income etc. – and to this end we explore many thousands of realisations of UK cities, demonstrating that in general for most reasonable city sizes, there is no superlinearity – that is defining economies of agglomeration is problematic, while London is a massive outlier. This suggests that the world of the UK cities at least is much more complex than the US, and that one explanation is that the UK is one large, relatively integrated urban system – city even – while the US is still composed of distinct cities that have not yet become integrated in quite the same way that has happened in the UK. We develop these ideas using various definitions of cities, particularly as networks of streets that we explore using percolation theory. Central to this talk is the notion that to explore city size and scale we need extensive data on transport and other networks defined at the finest resolution possible.
BIOGRAPHY | Michael Batty is Bartlett Professor at University College London where he is Chair of the Centre for Advanced Spatial Analysis (CASA). He has worked on computer models of cities and their visualisation since the 1970s and has published several books, such as Cities and Complexity (MIT Press, 2005) which won the Alonso Prize of the Regional Science Association in 2011, and most recently The New Science of Cities (MIT Press, 2013). His blogs (www.complexcity.info) cover the science underpinning the technology of cities and his posts and lectures on big data and smart cities (www.spatialcomplexity.info)
University of Birmingham
TITLE | Mining and Understanding Big (and Small) Mobile Data
ABSTRACT | Mobile phones are increasingly equipped with sensors, such as accelerometers, GPS receivers, proximity sensors and cameras, which, together with social media infromation can be used to sense and interpret people behaviour in real-time. Novel user-centered sensing applications can be built by exploiting the availability of these technologies. Moreover, data extracted from the sensors can also be used to model and predict people behaviour and movement patterns, providing a very rich set of multi-dimensional and linked data, which can be extremely useful, for instance, for marketing applications, real-time support for policy-makers and health interventions.
In this talk I will discuss some recent projects in the area of large-scale scale data mining and modelling of mobile data, with a focus on human mobility prediction and epidemic spreading containment. I will also overview other possible practical applications of this work, in particular with respect to the emerging area of anticipatory computing and the challenges ahead for the research community.
BIOGRAPHY | Dr. Mirco Musolesi is a Reader in Networked Systems and Data Science at the School of Computer Science at the University of Birmingham. He received a PhD in Computer Science from University College London in 2007. Before joining Birmingham, he held research positions at Dartmouth College and Cambridge and a Lectureship at the University of St Andrews. His research interests lie at the interface of different areas, namely ubiquitous computing, large-scale data mining, and network science. More information about his research profile can be found here.
University of Miami
Thursday 12th June 2014, 9:00am
TITLE | The Dark Side: Dynamics of Clandestine Social Networks
ABSTRACT | Even with ‘big’ data about a given social network, it is very hard to predict what behaviors might emerge in the future. However this problem becomes even more challenging for clandestine networks in which adaptation to survive combined with limited hierarchical control can generate a highly active temporal evolution. In this talk I analyze three complementary examples of such dark temporal networks — online activity surrounding the civil unrest ‘Springs’ in Latin America during 2013-2014, offline networks generating anti-government violence during the ‘Troubles’ in Northern Ireland during the period 1970-1995, and the recent explosion of networks of networks in the dark pools associated with high-speed financial trading. In each case, I examine the effect that operating in the dark seems to have on the network dynamics, and discuss consequences for the prediction of future behaviors in — and threats from — such systems.
BIOGRAPHY | Neil Johnson heads up the Complex Systems Initiative at the University of Miami, Florida, where he is also Professor of Physics. Before this, he was Professor of Physics for 15 years at Oxford University where he cofounded the CABDyN interdisciplinary research center on Complex Agent Based Dynamical Systems. He also cofounded the Oxford Center for Computational Finance (OCCF). He obtained his undergraduate degree from Cambridge University, and his PhD from Harvard University as a Kennedy Scholar. He has published more than 200 scientific research articles and two books (Financial Market Complexity and Simply Complexity) as well as serving on the Editorial Boards of many academic journals. In 1999 he presented the Royal Institution lectures on BBC television.
Institute for the Study of Labor
TITLE | Health and Well-Being in the Crisis
ABSTRACT | The internet has become an important data source for the Social Sciences because these data are available without lags, can be regarded as involuntary surveys and hence have no observer effect, can be geo-labeled, are available for countries across the globe and can be viewed in continuous time scales from the micro to the macro level. We use internet search data to document how the great economic crisis has affected people’s well-being and health studying the US, Germany and a cross section of the G8 countries. We investigate two types of searches, which capture self-diagnosis and treatment respectively: those that contain the words ’symptoms’ and ’side effects’. Significant spikes for both types of searches in all three areas (US, Germany and the G8) are found, which are coincident with the crisis and its contagion timeline.
BIOGRAPHY | Nikos Askitas is a Mathematician who has done research in topology (4-dimensional topology and classical knot theory) and whose current research interests span from the empirical i.e. the use of technology for socioeconomic research to the theoretical i.e. game theory and its applications to evolutionary theoretical biology and economics. Nikos is currently Head of Data and Technology at the Bonn based Institute for the Study of Labor. Nikos is a speaker of the German Data Infrastructure to the country’s Council for Social and Economic Data, he is the creator of a remote processing tool called JoSuA and the inventor of an annual European metadata conference, EDDI. Finally he is publishing a monthly business cycle leading indicator based on heavy truck toll data, called the Toll Index.
University College London
Thursday 12th June 2014, 11:50am
TWITTER | @oligotweet
TITLE | Computational Behavioural Genetics
ABSTRACT | Genetic and environmental variation affect all complex human traits and disorders. Recent large-scale genome-wide association studies have been successful in identifying some of the specific genetic variants associated with human behaviour, and we often assume these associations will hold true within the same population irrespective of age or environmental context. However, twin and family studies tell us that for some traits heritability increases throughout childhood and adolescence, a finding reflected at the molecular level by the changing effect sizes of individual genetic variants. In a similar way, exposure to different environments can change how our genetic variants express themselves. One of the major challenges of coming years will be understanding how we can engineer our environment to mitigate genetic risk of disease. But with ever-larger population samples, vast and increasing quantities of genetic data and the need for more detailed environmental exposure information, how can we hope to unravel the complex influences and interactions? I will give two examples of how our lab is addressing that challenge: the spACE project, which is using data from tens of thousands of twins to map the world’s genetic and environmental hotspots (http://sgdp.iop.kcl.ac.uk/davis/teds/geocoding/), and a new collaboration with Claire Haworth’s lab at Warwick (http://www2.warwick.ac.uk/fac/sci/psych/people/chaworth/) that is analysing millions of tweets to track genetic and environmental influences on wellbeing in emerging adulthood.
BIOGRAPHY | Oliver read biological Natural Sciences at Cambridge, specialising in Experimental Psychology. He went on to study for an MRC-funded MSc and PhD in Statistical Behavioural Genetics at the MRC Social, Genetic & Developmental Psychiatry Centre, King’s College London. Following his PhD he was awarded a Sir Henry Wellcome Fellowship to identify patterns of genome-wide association in the development of cognitive, behavioural and psychiatric disorders, spending time at the Wellcome Trust Centre for Human Genetics in Oxford, and at the European Bioinformatics Institute in Cambridge. In January 2013 he moved to UCL Genetics Institute, where he leads the London half of the Dynamic Genetics lab, developing new computational, statistical and visual analysis techniques, and applying them to datasets from large genetically informative population samples. The lab’s aim is to use big genetic and social data to unweave the nature and nurture of complex traits and common disorders throughout development.
Friday 13th June 2014, 11:25am
TITLE | Collaborative Social Sensing
ABSTRACT | One of the most profound technological phenomena of the last decade is the increasing blurring of boundaries between the digital and the physical world. We are currently witnessing the emergence of a connected, environment aware “digital ecosystem” encompassing anything from automotive electronics through home automation systems and service robots to an explosively growing volume of user generated online content related to the physical world (tweets, photos, videos etc.). The talk will discuss how the information present in such digital ecosystems can be leveraged to monitor, understand and influence social processes at different scales.
BIOGRAPHY | Paul Lukowicz is Professor of AI at the DFKI and Kaiserslautern University of Technology in Germany where he heads the Embedded Intelligence group. He holds an MSc. and a Ph.D. in Computer Science and a MSc. in Physics. His research focuses on context aware ubiquitous and wearable systems including sensing, pattern recognition, system architectures, models of large scale self organized systems, and applications.
Friday 13th June 2014, 11:25am
TWITTER | @pushmeet
TITLE | Learning to Interact (Naturally) with (All) Users
ABSTRACT | We have seen a dramatic rise in the use of computational devices/systems for our information and entertainment needs. The growing reliance on these technologies has motivated researchers to work on the development of “natural” user interfaces that can understand the intent and preferences of users and are easier to use. Digital assistants (Siri/Cortana), Search engines (Google/Bing), and Gaming consoles (Kinect/Nintendo Wii) are some popular examples. Making machines understand human intentions and preferences is an exceptionally challenging problem. Part of this difficulty lies in capturing the large variability in the preferences and behaviour of different users. Using examples from our work on personalized recommendation systems and Kinect-based gesture recognition interfaces, I will discuss the challenges of developing a system that is supposed to work on “everybody”.
BIOGRAPHY | Pushmeet is a senior researcher in the Machine Learning group at Microsoft Research where he works on projects in Computer Vision, Information Retrieval, Discrete Optimization, Crowdsourcing and Game Theory. Pushmeet has co-authored and co-edited a number of award winning technical papers and books in the fields of machine learning and robotics. His current research interests include personalized human computer interfaces, and the use of new depth sensors such as KINECT for the problems of human pose estimation, scene understanding and robotics.
University of Warwick
Thursday 12th June 2014, 10:05am
TWITTER | @robnprocter
TITLE | The Collaborative Online Social Media ObServatory: a progress report
ABSTRACT | I will outline the main features of the Collaborative Online Social Media ObServatory (COSMOS) and demonstrate their application through examples of research currently being undertaken by the COSMOS team. I will conclude with a brief overview of future development plans.
BIOGRAPHY | Rob Procter is Professor of Social Informatics in the Department of Computer Science, University of Warwick and Exchange Professor, NYU. One focus of his current work is methodologies and tools for big social data analytics. Rob led a multidisciplinary team working with the Guardian/LSE on the ‘Reading the Riots’ project, analysing tweets sent during the August 2011 riots. This won the Data Visualization and Storytelling category of the 2012 Data Journalism Awards and the 2012 Online Media Award for the ‘Best use of Social Media’.
Rob is founder member of the Warwick Institute for the Science of Cities (WISC), the UK partner of the NYU-led Center for Urban Science and Progress. Rob is also a co-founder of the Collaborative Online Social Media Observatory (Cosmos), a multidisciplinary group of UK researchers building a platform for social data analytics.
TITLE | The ongoing revolution in societal data
ABSTRACT | The digitization of society and proliferation of sensors are generating massive amounts of data reflecting human behavior. Such data are very different than those traditionally used in the social sciences, but are unique in their coverage, granularity, and variety. I will discuss the opportunities and challenges in extracting and interpreting information from such data, using in part examples from current CUSP research.
BIOGRAPHY | Steven E. Koonin was appointed as the founding Director of NYU’s Center for Urban Science and Progress in April 2012. That consortium of academic, corporate, and government partners will pursue research and education activities to develop and demonstrate informatics technologies for urban problems in the “living laboratory” of New York City.
Prior to his NYU appointment, Dr. Koonin served as the second Under Secretary for Science at the U.S. Department of Energy from May 2009 through November 2011. In that capacity, he oversaw technical activities across the Department’s science, energy, and security activities and led the Department’s first Quadrennial Technology Review for energy. Before joining the government, Dr. Koonin spent five years as Chief Scientist for BP plc, where he played a central role in establishing the Energy Biosciences Institute. Dr. Koonin was a professor of theoretical physics at California Institute of Technology (Caltech) from 1975-2006 and was the Institute’s Provost for almost a decade. He is a member of the U.S. National Academy of Sciences and the JASON advisory group.
Dr. Koonin holds a B.S. in Physics from Caltech and a Ph.D. in Theoretical Physics from MIT (1975) and is an adjunct staff member at the Institute for Defense Analyses.
University of Edinburgh
Friday 13th June 2014, 10:05am
TITLE | Social Sensemaking of Monitoring Data
ABSTRACT | Moving data out of the context in which it is gathered can make it difficult to interpret. We argue that a process of “social sensemaking” can help overcome this difficulty by enabling the transfer of some aspects of context when data is moved. We illustrate this by drawing on an example in telehealthcare and provide an outline of our current work on this problem.
BIOGRAPHY | Stuart Anderson is professor of Dependable Systems at Edinburgh. He works on socio‐technical systems, their resilience and how Social Science and Informatics provide a unique perspective on the conception, design, deployment and operation of computer‐based systems. Recently he established the Digital Health Institute at the University of Edinburgh, and work on Social Computation, Collective Adaptive Systems and their application in Digital Health.
University of Oxford
Thursday 12th June 2014, 4:35pm
TWITTER | @TahaYasseri
TITLE | Armies in the lab: Studying conflicts and opinion clashes in Wikipedia
ABSTRACT | Wikipedia is not only the largest online encyclopaedia ever, but also a notable example of internet-based collaborative value production. However, there are many unanswered questions about the mechanisms behind the process of article formation in Wikipedia, such as emergence and resolution of editorial wars. In this work, we try to locate, quantify, and understand the features of editorial wars in details. To this end, we focus on the network of editors of certain articles, who are connected by anti-collaboration links, i.e., reverting edits. Then we introduce a measure of controversy based on the parameters of the revert network, which ranks the articles according to the “amount of conflict” in them. We observe different scenarios of edit wars with various characteristics and ways to approach to consensus, which we successfully model in the agent-based-modelling framework. Finally, we try to reveal leader/follower relationships between editors and its effects on editorial wars as well as triangular closures between triples of editors.
BIOGRAPHY | Taha Yasseri (PhD in Physics) is the Big Data Research Officer at the University of Oxford’s Internet Institute (OII). Prior to the OII, he spent two years as a postdoctoral researcher at the Budapest University of Technology and Economics, working on the socio-physical aspects of the community of Wikipedia editors, focusing on conflict and editorial wars, along with Big Data analysis to understand human dynamics, language complexity, and popularity spread. He has interests in analysis of Big Data to understand human dynamics, government-society interactions, mass collaboration, and opinion dynamics within the framework of computational Social science. He has a PhD degree from university of Göttingen, Germany in complex systems physics.
Wednesday 11th June 2014, 3:45pm
TITLE | The Human Manifold: On the Predictability of Human Online Behaviour and its Consequences
ABSTRACT | We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for pre-processing the Likes data, which are then entered into logistic/linear regression to predict individual psycho-demographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait “Openness,” prediction accuracy is close to the test–retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy. This is joint work with Michal Kosinski and David Stillwell at the University of Cambridge and is based on the PNAS paper “Private traits and attributes are predictable from digital records of human behavior”.
BIOGRAPHY | Dr. Thore Graepel is a researcher at Microsoft Research Cambridge leading the Online Services and Advertising and Applied Games group, where their work is focused on the application of large scale machine learning and probabilistic modelling techniques to a wide range of problems including online advertising, web search, and games. He has a particular passion for the game of Go and the quest for developing a Go engine that plays as well as the best human players. More recently, he has been investigating crowdsourcing, collective intelligence and social networking data. Before joining the Cambridge lab of Microsoft Research, Thore was a postdoctoral researcher at the Department of Computer Science at Royal Holloway, University of London working on learning theory and machine learning algorithms with Prof. John Shawe-Taylor. Previous to that, he worked with Nici Schraudolph and Prof. Petros Koumoutsakos as a postdoctoral researcher at the Institute of Computational Science (ICOS) which is part of the Department of Computer Science of the Swiss Federal Institute of Technology, Zürich (ETH). Topics of research were machine learning and large-scale nonlinear optimisation. Dr. Graepel received his doctorate (Dr. rer. nat) from the Department of Computer Science of the Technical University of Berlin, where he was first a member of the Neural Information Processing group of Prof. Klaus Obermayer and later joined the Statistics group of Prof. Ulrich Kockelkorn.
University College London
TITLE | Incorporating street network effects in models of crime
ABSTRACT | The spatio-temporal distribution of crime in urban areas has been the subject of a large volume of empirical research, and is a topic with immediate relevance to policy. In recent years, a number of models have been proposed which seek to describe the occurrence of crime by encoding criminological theories of offender behaviour, and which may ultimately be used predictively. While these show promise in terms of their ability to generate characteristic patterns (such as hotspots), however, few such models take into account the influence of urban form; in particular, the effect of the street network. Using data from London and Birmingham, I will demonstrate that significant relationships exist at the street segment level between crime risk and a number of network metrics, including those intended to predict levels of use and awareness. I will discuss the implications of this for crime modelling, before introducing a model which is situated on a network and allows a number of these considerations to be accounted for. I will then show how the model can be used to explore a number of policy issues, related to policing and urban design, using both simulated and analytic results.
BIOGRAPHY | Toby Davies is a research associate in the Department of Civil, Environmental and Geomatic Engineering at University College London. After completing an MMath in Mathematics at the University of Oxford, he joined the SECReT PhD program at UCL, where he was co-supervised between the departments of Mathematics and Security Science. His research interests concern the use of approaches from complexity science in the context of crime; in particular, the measurement of space-time clustering, the influence of street networks on crime, and the evolution of large-scale riots. He now works on the Crime, Policing and Citizenship project at UCL, studying the interaction between crime occurrence, policing activity and public perception.
University of Warwick
TITLE | Telling Meaningful Stories with Data
ABSTRACT | The world’s data is growing. In 2011, we created almost 2 trillion gigabytes. Recent studies suggest online data can be used to improve forecasts of stock markets, track a crisis in real time, and glean new insights into an economy. Yet, we have no way for people to instantly explore and understand this enormous treasure. Here at the University of Warwick and University College London, we are building Tree: a data engine that lets you instantly explore online data, make remarkable discoveries and tell meaningful stories.
BIOGRAPHY | Adrian Letchford has spent his life on computers. Five years after high school, he had earned a Bachelor of Computer Science with 1st Class Honours and completed his Ph.D research. Adrian has worked on artificial intelligence, finance, veterinary science, agent based models and Australian national security. Currently at Warwick Business School, Adrian focuses on building software tools that connect online behaviour to the real world.
University of Manchester & University of Leeds
RCUK NEMODE Session — Friday 13th June 2014, 2:30pm
TWITTER | @anitaghill
TITLE | Wonders of the Zooniverse — understanding one million users, crowdsourcing and citizen science
ABSTRACT | Why do people contribute to online citizen platforms? What is their motivation? Can the understanding of online citizen science be used to build new business models? These are questions that take on major economic and social significance, considering the Zooniverse.org has over one million participants. The Zooniverse.org is a platform enabling the efforts and abilities of citizens along with scientists to analyse a flood of data. We are exploring the interface between citizen science and crowdsourcing. In our investigation we focus on the following: knowledge of the crowd; value of the crowd; and the motivations of the crowd. The research will generate evidence to demonstrate how managers of crowdsourcing initiatives can optimise both the user experience and their management approaches, in order to enhance and sustain levels of participation. This will ensure the self-preservation of their operational model. A key focus of the project is to discover how value is being captured by the Zooniverse, through the voluntary activities of labour, knowledge, skills and expertise. Further we will investigate how user value can positively contribute to participation in citizen science.
BIOGRAPHY | Dr Greenhill’s key areas of research interest are in the areas of Networked Usage of Technology within Community, Organisational and Business settings. She is actively conducting research into technologically enabled work, spatiality, and Internet usage in organisations. Dr Greenhill has a growing body of more than 60 publications, ranging from examination of virtual space and the impact that new technological developments are having on organisations and people to the use of technology on techno-religious practice. Dr Greenhill recently carried out a research project for the National Coordinating Centre of Public Engagement (NCCPE) examining the engagement practices between Universities and Local Communities. Dr Greenhill is currently a co-investigator on a NEMODE (EPSRC) 3 year project Modelling and optimising participation in online citizen science: Uncovering the wonders of the Zooniverse.
Dr Gary Graham is based at Leeds University Business School and is a founding member of the Future Cities and Community Resilience Network. This network is focused on the use of creative and cultural foresight techniques to map out a better social, economic and ethical future for ordinary people living in inner city communities. Gary is a visiting research scholar at the MIT Centre for Transport and Logistics and the Freight Future Lab. He has authored two books and guest edited three highly ranked special issues and reviews for TFSC, Futures, EJM and SCM: an International Journal.
RCUK NEMODE Session — Friday 13th June 2014, 3:15pm
TITLE | Business Models for Exploiting Technology and Social Connectivity
ABSTRACT | One of the biggest challenges faced by UK technologists and scientists is not scientific achievement but successful recognition and adoption of those achievements – whether they are computing devices, programmes, novel drugs, or novel machines. Similar challenges exist in the world of artistic creativity. The business model is a “device” or “configuration” that connects (a) creativity or technology with (b) customer satisfaction and (c) financial sustainability. Getting the business model right is the key to achieving recognition and monetization. This EPSRC project is uncovering how we should think of business models, how they can be better understood, and how they are successfully enacted. And the short talk will uncover the leading edge work in the area, progress that has been made and what it means for the community.
Themes of the talk will include how we should think of business models, what it means to “enact” a business models, the 4 core dimensions” of a business model: “Customers – who are they”, “Engagement – value proposition”, “Delivery – value chain”, and “Monetization – value capture”; and 4 basic “kinds of business models” – Product, Service, Two-sided, and Market Place. It will also show how we are building a library of examplars available on the web that will help mangers and scientists understand these types and how to mobilise them. And we will explain “business model innovation” that occurs when a firm chooses a new business model that challenges existing thinking.
BIOGRAPHY | Charles Baden-Fuller is a Strategic Management Society Fellow and Centenary Professor of Strategy at Cass Business School, City University London, and Senior Fellow at the Wharton School. He holds an EPSRC Grant named “Building Better Business Models”.
University of Warwick
RCUK NEMODE Session — Friday 13th June 2014, 2:15pm
WEB | http://www.ireneng.com
TWITTER | @ireneclng
TITLE | The HAT (http://www.hubofallthings.com)
ABSTRACT | The Hub-of-all-Things (HAT) is a £1.2m multi-disciplinary project funded by the Research Council’s UK Digital Economy Programme. It involves a team of 16 researchers from the domains of Economics, Business, Computing and the Arts across six UK universities of Cambridge, Edinburgh, Exeter, Nottingham, Warwick and the West of England. Starting in June 2013, HAT will create the first ever Multi-sided Market Technology Platform for the home. The HAT allows individuals to acquire data and build their own repository of horizontal, meaningful data that is useful for decision-making (contextualisation), and enables them to exchange data with firms for products and services. The HAT will create a horizontal platform that fits human lives, evolving into the next stage of the Internet; that of people and things. With an epic collision of vertical industries of manufacturing, service and Internet companies, new horizontal-type business and economic models that are human-centric is expected to emerge.
BIOGRAPHY | Irene Ng is the Professor of Marketing and Service Systems at the University of Warwick, leading the trans-disciplinary Service Systems Research initiative within the Warwick Manufacturing Group (WMG). Irene is involved in several government-funded research projects in the digital economy, including being the Principal Investigator of the RCUK Hub-of-all-Things (HAT) project as well as co-investigator of the RCUK New Economic Models of the Digital Economy (NEMODE) Network+ project. Prior to joining academia, Irene was an entrepreneur for 16 years as CEO of SA Tours, one of Southeast Asia’s largest tour operators, and the founder of Empress Cruise Lines, which she had built into a venture worth US$250 million in annual turnover when she sold it in 1996. Since becoming an academic in 1997, Irene has received global recognition for her work in value, new business models and service systems, with 22 journal articles, three books and national appointments such as the ESRC /AIM Services Fellow in 2008 and ESRC /NIHR Fellow in 2009. Her latest book Creating New Markets in the Digital Economy was recently published by Cambridge University Press in early 2014 Irene’s research lies in the transdisciplinary understanding of value; understanding, creating, designing, pricing, contracting and innovating based on value, as well as new business models and value co-creation in complex service systems.
University of Cambridge
RCUK NEMODE Session — Friday 13th June 2014, 3:00pm
TWITTER | @LM367
TITLE | Bit by bit: Capturing value from the digital fabrication revolution
ABSTRACT | Digital fabrication (which includes processes termed ‘additive manufacturing’ or ’3D printing’) is thought by some commentators to be underpinning a potential manufacturing revolution. Covering a broad range of technologies, digital fabrication offers the prospects of on-demand, mass personalisation, with more localised, flexible and sustainable production. These technologies have the potential to disrupt the organisation of manufacturing and the ways in which companies create and capture value. This programme of research aims to: (1) address key research questions relating to the emergence of digital fabrication and its impact upon the UK economy, and (2) deliver an enduring cross-disciplinary research platform for responding to future digital economy-related research challenges.
BIOGRAPHY | Letizia Mortara is a Senior Research Associate at the University of Cambridge. She joined the IfM’s Centre for Technology Management as a Research Associate in 2005. Prior to this she gained her first degree in Industrial Chemistry at the University of Bologna in Italy. After spending three years working as a process/product manager in the chemical industry, she moved to the UK where she gained her PhD in processing and process scale-up of advanced ceramic materials at Cranfield University. Letizia’s research centres on understanding how companies could keep abreast with the latest developments in technology and how they can adopt an open approach to innovate.Together with colleagues Simon Ford and Tim Minshall, she is currently focusing on Digital Fabrication technologies in manufacturing and their implications for business. Letizia will describe this project, “Bit by bit: Capturing value from the digital fabrication revolution” reporting on its aims and observations to date.
University of Exeter
RCUK NEMODE Session — Friday 13th June 2014, 1:45pm
BIOGRAPHY | Roger Maull is a Professor of Management in the University of Exeter Business School. He has a BA in Economics, and an MSc in Management Information Systems. He gained his PhD in 1986 in the use of systems modelling (IDEF0) in manufacturing. His research interests are in applying systems thinking to the management and design of service organisations, in particular those problems that are at the nexus of marketing, operations, IT and HR. At the centre of his research is the question “how do we design service systems?”
Service processes occur because of the introduction of the “customer into the works” (Frei 2006). They are open systems often with high variety sometimes with known unknowns or even unknown unknowns. These processes provide fundamentally different problems from those in manufacturing where modelling is often deterministic or probabilistic. Roger is particularly interested in the characteristics of service variety and his dominant theoretical lens is Ashby’s law of requisite variety which states that the regulator must be able to match the variety in the disturbance in order for the system to be viable. In April 2012 he was awarded an RCUK Network grant (£1.5M) to lead research into the issues surrounding the impact of the digital economy on new economic models (NEMODE). This places the questions of service design within the context of a rapidly changing technological landscape. Since the launch of NEMODE Roger has become increasingly interested in the opportunities for service design arising from ‘big data’. He conceptualises this research domain into three areas: collecting the data eg sensors and mobiles; analysing the data through new statistical methods; using the analysis to inform new business models. The third stream is of particular interest and he has been successful as part of a large consortium of researchers in bidding for on-going RCUK funding (£928k) in looking at how ‘big data’ might transform individuals ability to use their own data in the ‘HAT’ project.
Roger has developed and delivered a wide range of systems modelling courses for companies such as Vodafone, Woolwich, IBM, ICL, Rank Xerox, GKN/Westland Aerospace, LloydsTSB, Scottish Amicable Scottish Power, British Aerospace, Motability Finance Ltd, DuPont, Fujitsu, Prudential and Sprint PCS. He has been awarded international grants to work with industry in the USA, Australia, Germany and Italy and is currently a Visiting Professor at the Australian Business School at UNSW. He has successfully supervised 18 PhD students and examined 19 PhDs.
University of Southampton
RCUK NEMODE Session — Friday 13th June 2014, 2:45pm
TITLE | Here Be Dragons: Initial Findings of the EPSRC Meaningful Consent Project
ABSTRACT | This paper will outline the initial findings of an EPSRC-funded multidisciplinary workshop on the challenges of establishing and managing meaningful consent in the context of digital transactions, conducted with an international panel of participants representing technology, business and policy perspectives, and tasked with mapping the current landscape and outlining the future research agenda. The first part of the workshop explored the current ‘Landscape of Consent’ from separate Technology, Policy and Business perspectives, identifying a profound lack of transparency in digital transactions as a major problem from all perspectives. The specific domain challenges for technology, policy and business are examined. The second part of the workshop focused on the clarities, uncertainties and priorities for research, concluding that the problems are certainly significant and international, with uncertainty grouped around three principal axes: Technology and Data, People, Rights and Ethics, and the Management of Regulation. New research needs were identified in at least three major areas: New Business Models, Technologies and Implementation, and New Directions in Policy. Further unknowns highlighted included the economic and business value of online privacy and digital consent, the taxonomy of consentable transactions, the scope for assistive technologies to automate and assist consent management, and the behavioural economics of consent. The combination of these unknowns frames a grand challenge in assessing the implications of consent for technology, economics, business and policy.
BIOGRAPHY | Dr. Stephen Rhys Thomas is a former Cambridge neuroscientist with two decades’ experience in the high-tech and bio-tech sectors, where he was the originator of numerous corporate technology and business strategies at world-class, research-driven, complex-system businesses, including Merck & Co., Hewlett Packard Laboratories, GSK, Oracle and Accenture. He has worked and consulted in all phases of innovation from discovery through marketing to implementation, in research, technical, executive, and consultative roles, and has brought $100m global software products to market. Over the past decade he has been a Partner or founder in both mainstream and niche consulting companies serving blue-chip and start-up clients in the high-tech and bio-tech sectors, and is a qualified Member of the Institute of Directors. He joined the School of Management from industry to pursue research into Technology Innovation and Digital Marketing; current research projects include Barriers to Open Innovation in Biotech, and Broken Models, a study of Disintermediation Candidates in the Digital MarketSpace.
PRESENTER | Ansgar Koene (University of Birmingham)
TITLE | Adjustment to partner behaviour during social interaction
ABSTRACT | Human day-to-day existence typically involves an almost endless stream of mutual anticipation, adjustment and negotiation, consciously through verbal communication but also, far more pervasively, through unconscious adjustments in our motor behaviour. Simple actions, such as walking down a crowded street, or handing objects to each other, require continuous feedback to identifying what other people are about to do and adjust accordingly. As part of the CogLaboration project (www.coglaboration.eu), in which we are developing a service robot for fluent Human-Robot object handover, we quantitatively study and model the way in which people adjust mutually adjust their behaviour to each other. Here we present the results from two studies in which participants negotiated a common interaction position in 3D space that was not extrinsically specified, during joint pointing and object handover respectively.
PRESENTER | Eric Jensen (University of Warwick)
TITLE | Automating market and audience research using smartphone apps, sentiment analysis and smile detection
ABSTRACT | Qualia is an ambitious project that has developed an open source smartphone app, sentiment analysis tool and web engine for analysing audience feedback and evaluation. The project involved developing and critically evaluating the utility and validity of evaluation using automated smartphone apps, sentiment analysis tailored to cultural audience data and other tools. The system allows digital data to be easily and inexpensively used by cultural institutions to assess audience responses in real time, as well as tracking audience responses over time (e.g. over the course of a festival or museum visit). It also critically engages with a growing call for greater use of mobile technologies in cultural institutions. Qualia-generated results have been refined and tested using conventional social scientific evaluation methods (e.g. at the Cheltenham Science Festival). The project is funded by the Nesta, the AHRC and Arts Council England through the Digital R & D Fund for the Arts.
PRESENTER | Kavin Preethi Narasimhan (Queen Mary)
TITLE | Agent Clusters: Simulations of Human Conversational Groups
ABSTRACT | Conversational clusters refer to groups of two or more people engaged in face-to-face interaction. The proposed work uses simulations to account for the spatiality of conversational clusters. Ethnomethodological studies regard the spatial manifestation of conversational clusters as an emergent phenomenon. But computational models consider circularity as a governing factor for the synthesis of conversational clusters. The proposed research is a case study of these juxtaposed ideologies. To this end, two different agent-based models are implemented: Model 1 intentionally contrives agents into forming circular clusters. Model 2 on the other hand, motivates nearby agents to maximize their visual access to one another. The spatial manifestations of clusters resulting from Models 1 and 2 are then statistically compared with video data of naturally occurring conversational clusters. Comparison shows that Model 2 performs better than Model 1 in simulating organic-looking agent clusters.
PRESENTER | Maria Liakata (University of Warwick)
TITLE | SentiAdaptron — A domain adaptable sentiment analyser for Twitter
ABSTRACT | This work will present SentiAdaptron – a Twitter sentiment analyser with a particular emphasis on cross-domain adaptation – and discuss the various challenges involved in its creation such as gathering a corpus of tweets representing three different domains (finance, politics, technology), choosing appropriate classification techniques for intra- and inter-domain classification and domain adaptation and finally performing intrinsic as well as extrinsic evaluation of its usefulness in predicting sentiment, with the latter including political polls for Obama and the Republican and Democrats parties, and competitive theoretical trading performance on stocks and stock market indices.
PRESENTER | Marzieh Saeidi (UCL)
TITLE | Urban Knowledge Extraction
ABSTRACT | Geo-spatial prediction for urban neighbourhoods is a fundamental problem for science, industry and policy makers. For example, it is important to predict the deprivation of an urban neighbourhood, its trendiness or the likelihood that a customer would like to live there. Generally such tasks can be formulated as classification or regression problems, provided we have access to a source of annotated gold data and a rich set of features to represent neighbourhoods. With the advent of social media, urban sensors, and big data we now have access to an unprecedented amount of potential features from data sources such as yelp, yahoo answers and more. In this work for the first time we attempt to make predictions on urban areas’ characteristics. We use generic feature vectors that do well in all the prediction tasks and are obtained from processing social media data and mainly text.
PRESENTER | Sam Devlin (University of York)
TITLE | Game Intelligence
ABSTRACT | Game Intelligence is knowledge gained by the player or by analysing the data players generate by playing digital games. Given the digital nature of modern video games and the growing ubiquitous presence of an internet connection, the analysis of vast quantities of gameplay data is now possible. In particular, the recent growth in mobile and casual (e.g. Android, iOS, and Facebook) games provide a new tool yielding a major step-change in experimental studies of human behaviour; moving from small samples to potentially huge numbers of participants. This data can help us to understand individual behaviour and preference on a hitherto impossible scale, making it feasible to use all modern video games as a powerful new tool to achieve our scientific and societal goals.
PRESENTER | Sam Martin (University of Warwick)
TITLE | The Digital Coeliac: Twitter, the City and the Gut.
ABSTRACT | My doctoral research explores how individuals’ online interactions inform their health-navigation of the city. With the case study of coeliac disease, my research aims to visualise the flow of patient interaction through Twitter to detect patterns of decision-making and risk-aversion, by creating a virtual map of Big Data health annotations comparing the cities of London and New York.
PRESENTER | Rob Procter (University of Warwick)
TITLE | COSMOS
ABSTRACT | The COSMOS objective is to establish a coordinated interdisciplinary UK response to Big Social Data. It is developing a research programme to address next-generation research questions that focus upon the challenges posed by big social data to government, digital economy, security & privacy, and civil society, that will form an evidence base to lead policy development and practice. This empirical programme is complemented by a focus on the ethical impact dimensions of big social data and the development of new methodological tools and technical/data solutions for UK academia.
PRESENTER | Weisi Guo (University of Warwick)
TITLE | Emotion Sensing using heterogeneous mobile phone data
ABSTRACT | This project (in collaboration with CUSP, NYU, funded by a Warwick RDF and IBM) uses textual data entered by users in their mobile phones as a proxy for their emotions, in conjunction with information about their physical location and digital landscape, so as to understand the effect of the environment on emotional fluctuation. The prototype study is taking place in NY. We also plan to calibrate our results against the Warwick-Edinburgh mental well-being scale (WEMWBS). We anticipate that the results from this study will (a) provide an effective, relatively non-invasive means for monitoring emotional fluctuation, with potential in helping personalized mental health management (b) will allow us to understand what types of interventions in cities may be beneficial in addressing environmental factors affecting people’s mood. In the near future we plan to expand this study to other cities around the world (Abu Dhabi, Mumbai, Athens, Beijing).
PRESENTER | William Lawrence (University of Southampton)
TITLE | The investor decision making process – A web science perspective
ABSTRACT | This project aims to better understand how decision making processes are influenced by online information. This will be assessed by searching for examples of decision making biases by individual traders under exposure to differing online information. This poster will outline some of the potential methods of achieving this as well as introducing the aims of future work.