April 30, 2018 — Workshop acceptance notification.
May 9, 2018 (extended to May 13 for abstracts, May 20 for final versions) — Full paper & short paper submission deadline.
June 19, 2018 — Notification of acceptance.
July 24, 2018 — Camera-ready version.
September 10, 2018 — Late registration.
September 25, 2018 — Workshop day.
September 26-28, 2018 — Main conference dates.
All the deadlines are at 23:59:59 Hawaii Time.
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April 9, 2018 Workshop proposal submission deadline
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April 30, 2018 Workshop acceptance notification
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May 9, 2018 (ext. to May 13 for abstracts, May 20 for final versions) Full paper & short paper submission deadline
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June 19, 2018 Notification of acceptance
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July 24, 2018 Camera-ready version
Early-bird and cut-off registration -
Sept. 10, 2018 Late registration
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Sept. 25, 2018 Workshop day
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Sept. 26–28, 2018 Main conference dates
About
Mission
We are delighted to welcome the 10th International Conference on Social Informatics (SocInfo 2018) to St.Petersburg, Russia, On September 25–28, 2018.
SocInfo is an interdisciplinary venue for researchers from Computer Science, Informatics, Social Sciences and Management Sciences to share ideas and opinions, and present original research work on studying the interplay between socially-centric platforms and social phenomena. The ultimate goal of Social Informatics is to create better understanding of socially-centric platforms not just as a technology, but also as a set of social phenomena. To that end, we are inviting interdisciplinary papers, on applying information technology in the study of social phenomena, on applying social concepts in the design of information systems, on applying methods from the social sciences in the study of social computing and information systems, on applying computational algorithms to facilitate the study of social systems and human social dynamics, and on designing information and communication technologies that consider social context.
Sponsors
Social Informatics Steering Committee
Karl Aberer, EPFL, Switzerland
Katsumi Tanaka, Kyoto University, Japan
Anwitaman Datta, Nanyang Technological University, Singapore
Ee-Peng Lim, Singapore Management University, Singapore
Noshir Contractor, Northwestern University, US
Hsinchun Chen, University of Arizona, US
Sue B. Moon, KAIST, Korea
Andreas Ernst, University of Kassel, Germany
Andreas Flache, University of Groningen, Netherlands
Dirk Helbing, ETH, Switzerland
Keynote Speakers
Ingmar Weber
Ingmar Weber is research director of the Social Computing Group at Qatar Computing Research Institute. His interdisciplinary research looks at what online user-generated data can tell us about the offline world and society at large. He works with sociologists, political scientists, demographers and medical professionals and several of his projects have been covered by international media. Prior to joining QCRI, Ingmar Weber was a researcher at Yahoo! Research Barcelona. He holds a BA & Ma from Cambridge and did his PhD at the Max-Planck Institute for Computer Science. He is one of ACM’s Distinguished Speakers and his keynote is financially supported by ACM.
Jonathan J. H. Zhu
Jonathan Zhou is Chair Professor of Computational Social Science and Director of Center for Communication Research and Web Mining Lab at City university of Hong Kong. His current research projects focus on how to use computational methods to mine and model time-bound user behavior on social and mobile media. He teaches new media theory (diffusion, use, and impact), quantitative methods (survey, experiment, content analysis, text mining, and network analysis), and new technologies (web, databases, and big data analytics).
Harith Alani
Harith Alani is a professor at the Knowledge Media institute, The Open University, where he leads a group specialising in social data analysis and web science research. His work is focused on analysing social media content and networks to detect, monitor, and predict online information and behaviour. Prof Alani is the co-ordinator of COMRADES (2016-2019); a €2M European H2020 project to research and develop a collaborative platform for supporting communities during crises, which incorporates automated methods for processing and linking of crowdsourced information and for safeguarding communities during critical scenarios from uninformative, distrusted, and fragmented information posted about the crises on social media. Prof Alani published over 140 scientific papers in various leading journals and conferences, and recently was research track co-chair at The Web Conference (WWW 2017) and at the Extended Semantic Web Conference (ESWC 2017).
Bettina Berendt
Bettina Berendt is a professor in the research group “Declarative Languages and Artificial Intelligence” (DTAI) at the Department of Computer Science of KU Leuven. Her research focuses on Web Mining and its uses and implications. Methodologically, she combines aspects of Web content, Web usage and Web structure mining with methods from the social and behavioural sciences relevant to the respective research questions and applications. The Web materials and platforms include Social Media such as microblogging or social networking sites, as well as (mainstream or other) news sites and the relation between these various channels of information. Research questions include privacy, the public and the private and the role of media in them, information literacy, and how data mining can be developed and deployed in a user-centric fashion for user empowerment in these areas.
Alexander Boukhanovsky
Alexander Boukhanovsky is the Director of School of Translational Information Technologies and the Head of Department of High Performance Computing at ITMO university, St.Petersburg. He is also the Chief Research Associate at the ITMO EScience Institute – a center for computationally intensive interdisciplinary research in a large number of areas, from social to natural science. His research interests range from high-performance and parallel computing to decision support & early warning systems, computational social science & human physiology modeling.
Olga Megorskaya
In Yandex, she is responsible for training data collection in all machine learning projects, as well as for mass infrastructure services development: technical support, SMM, call centers, translations, manual crowd testing and others.
She will talk about how Yandex employs crowdsourcing, about the basic principles of building production pipelines, and also about the research and mathematical tasks lying at the heart of work with crowds.
Programme
Programme
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Workshops
Multiplex networks are one of the most popular network analysis models that have been a common meeting point for computer scientists, physicists and sociologists thanks to their ability to provide richer, more qualitative information than simple graphs but still allow quantitative processing. The workshop will provide a practical introduction to multiplex network analysis using R. It will consist of very brief theoretical presentations of major concepts followed by practical tasks.
The main topics covered will be:
- visualization;
- actor measures (degree, neighborhood, ...);
- actor/layer measures (layer relevance, ...);
- layer comparison methods;
- community detection (generalized Louvain, LART, clique percolation, ...);
- generative models.
Associate professor
InfoLab Department of Information Technology
Uppsala University
Associate professor
Digital Design Department
Data Science & Society Lab (Coordinator)
IT University of Copenhagen
Topic modeling is one of the few algorithms capable to work with large textual data bringing together scholars from fields of social and computer sciences. However, practical applications of the algorithm are hindered by rarely discussed inherent limitations of topic models and the requirement of programming skills. In this workshop, we will address the specifics of using topic modeling in sociology, discuss mathematical limitations behind the method and introduce new TopicMiner and WebTopicMiner software. The proposed approach is designed to be inclusive of participants with no programming background bridging together communities from social and computer sciences.
The main workshop topics include:
- review of topic models;
- the stability problem of topic models;
- the problem of choosing the number of topics;
- regularization of topic models;
- comparison of topic solutions;
- topic modeling with TopicMiner and WebTopicMiner.
Associate professor
Deputy Head at Internet Studies Lab
Higher School of Economics, St. Petersburg
This course introduces participants to the collection and analysis of socially-generated big data using the R statistical software. The main emphasis is on applying social network analysis and quantitative text analysis to web data (especially social media). Data will be collected using the vosonSML R package (currently it collects YouTube video comment data, Facebook fan page data, and Twitter data). The course includes basic social network analysis in R/igraph (graph visualisation, core node- and network-level metrics, network clustering, constructing two-mode networks) and basic text analysis (building a corpus, descriptive analysis, wordclouds). The course will appeal to social scientists who want to become more computationally literate, and those from technical disciplines (e.g. computer science, information science) who would like to learn how social scientists are analysing digital trace data from the web.
The target audience for this course is research students, academics and researchers with a fairly strong technical background. It is preferable that students have had some exposure to social network analysis and quantitative text analysis. Experience with R or other programming languages is also desirable, but the course includes a brief R and RStudio refresher. It will be assumed that participants already have a recent version of R and RStudio installed on their laptops.
Associate professor, School of Sociology at the Australian National University
Head at Virtual Observatory for the Study of Online Networks Lab
Podium discussion “How access of researchers to privately collected data should be regulated?”
The starting point for this discussion is the recent scandal with Cambridge Analytica – a company that allegedly influenced the US presidential elections by manipulating Facebook users’ personal data. This data is said to have been leaked to Cambridge Analytica by Alexander Kogan, a researcher working at the core of the global academe – the university of Cambridge – and allegedly having ties with Russia. This breach has eventually resulted in closure of many Facebook data access opportunities for researchers worldwide. A panel of competent discussants, including representatives of both the academe and the data industry, will touch different aspects of the problem and possible solutions. The panelists will discuss whether it is possible to simultaneously protect individual privacy, provide enough data for public interest research, ensure opportunities for data related business and exclude opinion manipulation. Prior to the discussion, you can find more information on the scandal in the statements of Mark Zuckerberg, Alexander Kogan, Cambridge Analytica and the university of Cambridge.
Discussants:
Yanina Ledovaya
Senior lecturer in psychology, St.Petersburg University. Dr. Ledovaya has been recently working as a researcher and acting PI in the research project on prediction of psychological traits with Facebook data that has attracted international media attention amidst the Cambridge Analytica scandal as an alleged “link” of Alexander Kogan to Russia.
Vladimir Suvorov
Founder of SD Data Laboratory for Innovation Development; prior to that - Head of R&D team at EMC2 Skolkovo. SD Data is a data-based startup working in the field of artificial intelligence for virtual assistants and bioinformatics. Mr. Suvorov has a vast experience in working with big data, including sensitive data, as a senior executive both in a large corporation and in a small startup. He will talk about his vision of business risks and benefits of sharing data with researchers.
Jonathan Zhu
Chair Professor of Computational Social Science and Director of Center for Communication Research and Web Mining Lab at City university of Hong Kong. Professor Zhu is one of the signatories of the open letter entitled “Facebook shuts the gate after the horse has bolted, and hurts real research in the process”. This letter criticizes the new Facebook initiative to change researchers’ access its data from open APIs to an expert-review process for failure to provide sufficient support for transparent and independent scientific research.
Bettina Berendt
Professor at the Department of Computer Science, KU Leuven, Belgium. Prof. Berendt has led research that involved extracting data from Facebook with the purpose of helping users to better protect their privacy, and she has investigated the implications of personality tracking on privacy and societal fairness. Currently, she also studies links between AI and diversity and misinformation in news media. She will reflect on lessons learned for data access from these different but complementary perspectives.
Posters
You have to bring your poster printed out on A1 format. We will provide the equipment to hang up your poster.
Your poster should tell something about your current research and scientific interests. The main idea is for all summer school attendees to get to know each other both personally and in terms of scientific orientation.
Poster session will be held during two days. Posters should be formatted into A1 sheet (841×594 mm).
In general, posters combine textual and graphical representation of your work. The idea is to explain in easy-accessible way your results to the audience. During the poster session time you are expected to stay close to your poster to address questions and explain in a verbal way your ideas to other participants.
Organizers
Organizing Committee
