Workshop program

Full Day Workshops

W1: Beyond Online Data: Tackling Challenging Social Science Questions
Michael Macy; Daniel M. Romero; Amit Sharma; Chenhao Tan

W2: International Workshop on Misinformation in the Digital World (MDW18)
Mahdi Bohlouli; Nikos Sarris; Jochen Spangenberg

Half Day Workshops

W3: The Third International Workshop on NEws and publiC Opinion (NECO 2018)
Jisun An; Haewoon Kwak; Fabrício Benvenuto

W4: Bridging the Gaps: Social Media, Use and Well-being
Megan French; Xun "Sunny" Liu; Samuel Hardman Taylor; Eden Litt

W5: Data-Driven Personas and Human-Driven Analytics: Automating Customer Insights in the Era of Social Media
Jim Jansen; Joni Salminen; Lene Nielsen; Matti Mäntymäki

W6: Algorithmic Personalization and News: Risks & Opportunities
Juhi Kulshrestha; Cornelius Puschmann; Nicolas Diakopoulos; Aniko Hannak

W7: Social Media and Health: A Focus on Methods for Linking Online and Offline Data
Yelena Mejova; Rumi Chunara; Kyraki Kalimeri; Michael Paul

W8: 1st International Workshop on Emoji Understanding and Applications in Social Media (Emoji 2018)
Sanjaya Wijernatne; Emre Kiciman; Horacio Saggion; Amit Sheth

W9: 1st International Workshop on Chatbot
Ying Ding; Bing Liu; James Shanahan; Jie Tang

W10: Computational Social Science of Innovation Diffusion and Evolution (C-SIDE)
Tim Weninger; Nathan Hodas; Svitlana Volkova; Emily Grace

W11: Making Sense of Online Data for Population Research
Lee Fiorio; Emilio Zagheni; Afra Mashhadi; Bogdan State; Dennis Feehan

W12: Designed Data for Bridging the Lab and the Field: Tools, Methods, and Challenges in Social Media Experiments
Dominic DiFranzo; Natalie Bazarova; S. Shyam Sundar; Jeff Hancock

W13: 3rd International Workshop on the Social Web for Environmental and Ecological Monitoring (SWEEM)
Darian Frajberg; David J. Crandall

W14: Exploring Ethical Trade-Offs in Social Media Research
Casey Fiesler; Stevie Chancellor; Katie Shilton; Jessica Vitak; Michael Zimmer

W15: The 3rd International Workshop on Event Analytics using Social Media Data (EASM)
Yuheng Hu; Yu-Ru Lin

Details about each workshop are below.

W1: Beyond Online Data: Tackling Challenging Social Science Questions

The abundance of online data has provided exciting opportunities for computational social science. However, most social processes thrive at the intersections of online and offline worlds. It thus becomes necessary to connect online studies to the offline world, especially for tackling broad social science questions such as information access, education, healthcare, migration, discrimination, and poverty. This ICWSM workshop on "Beyond online data" aims to bring together social scientists and computer scientists to think about new ways to utilize data for addressing challenging social science questions. This includes novel ways of utilizing offline data, combining offline and online data, and creating new data through observation and experiments. Instead of starting with available datasets, the workshop will discuss approaches that start with a substantive question and find possible ways to leverage diverse potential datasets, including both online data and offline data.

  • Michael Macy, Cornell University
  • Daniel M. Romero, University of Michigan
  • Amit Sharma, Microsoft Research
  • Chenhao Tan, University of Colorado Boulder

W3: The Third International Workshop on NEws and publiC Opinion (NECO 2018)

Computational study of journalism has been an emerging discipline in recent years. A lot of inspiring data-driven studies on news production and consumption, news audience, news bias, and tools have been published and discussed. On the other hands, social media has received a lot of attention from researchers who study public opinion. The data collected from social media is a valuable asset to see what people have in their mind about at the very moment. Election prediction based on Twitter is a good example of such efforts. In this workshop, we are trying to make this two disciplines meet. How news media formulate public opinion and how public opinion influences on news media are our questions to ask. For this, of course, the parallel efforts on the understanding of news media and public opinion are required first and then based on the findings, we can look into the interplay between them. As a result, the workshop topics can be categorized into three groups: news, public opinion, and their interplay.

  • Jisun An, Qatar Computing Research Institute, HBKU
  • Haewoon Kwak, Qatar Computing Research Institute, HBKU
  • Fabrício Benevenuto, Federal University of Minas Gerais

W4: Bridging the Gaps: Social Media, Use and Well-being

There has been a wealth of recent reviews, meta-analyses, and empirical studies on the relationship between social media and well-being. However, scholars still have a limited understanding of how and why social media influences and relates to well-being. In this half-day workshop, academic and industry researchers will engage in cooperative problem-solving activities around the current state of social media and well-being to identify open questions and brainstorm design solutions. The overall goals of this workshop are to 1) foster discussion in order to bridge gaps and map future directions and 2) share the day's discussion with the field more broadly.

  • Megan French, Stanford University
  • Samuel Hardman Taylor, Cornell University
  • Eden Litt, Facebook
  • Sunny Xun Liu, Stanford University

W5: Data-Driven Personas and Human-Driven Analytics: Automating Customer Insights in the Era of Social Media

The workshop deals with the use of online analytics data for automating customer insights. An example of such an approach is automatic persona generation, in which social media data is retrieved via application programming interfaces (APIs), analyzed automatically with computational techniques, and presented to users of customer analytics via an online system. Even though automation of customer analytics includes a myriad of benefits, automation has been questioned as algorithms may pose bias and result in stereotypical or non-meaningful data portrayals. Thus, this workshop also explores the duality of data- and human-driven analytics. While data-driven analytics is focusing on the accuracy and availability of data to support decision making, human-driven analytics is defined as presentation and analysis of insights about users or customers that highlights qualitative attributes over numbers. We welcome all research papers/proposals that deal with the promises and challenges of automation of customer analytics, including the above-mentioned themes of techniques and mentality of automation.

  • Bernard J. Jansen, Hamad Bin Khalifa University
  • Joni Salminen, Hamad Bin Khalifa University; University of Turku
  • Lene Nielsen, IT University Copenhagen
  • Matti Mäntymäki, University of Turku

Algorithmic Personalization and News: Risks & Opportunities

Algorithms play a crucial role in how citizens around the world inform themselves about current affairs. According to the 2017 Reuters Digital News Report, an increasing number of users globally rely on personalization algorithms to receive news both directly on news websites, as well as indirectly via their algorithmic social media feeds, search engines, and news aggregators. In tandem with this development, there are growing concerns about the impact of algorithmic personalization on society in areas such as public opinion formation and viewpoint diversity on controversial issues. This workshop aims to broaden the debate on algorithms and news to discuss both risks and opportunities of personalization for news consumption and to develop suitable methods for auditing algorithmic personalization and its impact on users’ news consumption behaviors. It also aims to foster a dialogue between the stakeholders involved by bringing together researchers from computer science, media studies, journalism and communication sciences, as well as industry practitioners from both mainstream media and startups.

  • Juhi Kulshrestha, Max Planck Institute for Software Systems
  • Cornelius Puschmann, University of Hamburg
  • University of Hamburg, Northwestern University
  • Aniko Hannak, Central European University

W8: 1st International Workshop on Emoji Understanding and Applications in Social Media (Emoji 2018)

Pictographs, commonly referred to as "emoji", have become a popular way to enhance electronic communication. With their introduction in the late 1990's, emoji have been widely used to enhance the sentiment, emotion, and sarcasm expressed in social media messages. They often play distinct social and communicative roles compared to other forms of written language while taking over language constructs such as slang terms and emoticons. The ability to automatically process, derive meaning, and interpret text fused with emoji will be essential as society embraces emoji as a standard form of online communication. Yet the pictorial nature of emoji, the fact that (the same) emoji may be used in different contexts to express different meanings, and that emoji are used in different cultures and communities over the world who interpret emoji differently, make it especially difficult to apply traditional Natural Language Processing (NLP) techniques to analyze them. To meet these challenges, Emoji2018 aims to stimulate research on understanding social, cultural, communicative, and linguistic roles of emoji and developing novel approaches to analyze, interpret and understand emoji and their usage in social media applications. It provides a forum to bring together researchers and practitioners from both academia and industry in the areas of social network analysis and mining, natural language processing, computational linguistics, human-computer interaction, and computational social sciences to discuss high-quality research and emerging applications, to exchange ideas and experience, and to identify new opportunities for collaboration.

  • Sanjaya Wijeratne, Kno.e.sis Center, Wright State University
  • Emre Kiciman, Microsoft Research
  • Horacio Saggion, Universitat Pompeu Fabra
  • Amit Sheth, Kno.e.sis Center, Wright State University

W9: 1st International Workshop on Chatbot

  • Ying Ding, Indiana University
  • James Shanahan, Native X
  • Bin Liu, University of Illinois at Chicago
  • Jie Tang, Tsinghua University

W10: Computational Social Science of Innovation Diffusion and Evolution (C-SIDE)

Although diffusion of ideas and memes has a rich history in quantitative social science, online platforms such as GitHub and stack overflow provide a unique view into innovation and collaboration at a global scale. What does the behavior on online collaborative platforms tell us about how people leverage the help of others to create innovation and choose which technology to adopt? This workshop seeks to compare and contrast the diffusion of traditional social media information e.g., on Twitter, Facebook, Instagram with diffusion of technical approaches and software innovations. Because utilization of technical collaboration platforms arises from different user needs than traditional social media, behavioral models may require revalidation in this alternative context. We will explore behavioral models that may be specific to platforms such as GitHub, and we will discuss ways of adapting existing social-media based models to these technical tasks.

  • Nathan Hodas, PNNL
  • Svitlana Volkova, PNNL
  • Emily Grace, PNNL
  • Tim Weninger, Notre Dame

W12: Designed Data for Bridging the Lab and the Field: Tools, Methods, and Challenges in Social Media Experiments

This workshop will explore the methodological middle ground between the field and the lab. Research using repurposed observational data from online platforms has transformed the study of online behavior and have high external validity, but present challenges for establishing causality and replication. On the other hand, experimental studies offer high internal validity, discovery of causal relationships, and ease of replication, but the rigid control over the settings and interactions of an experiment can limit generalizability. New methods work toward bridging these two research contexts, bringing the lab to the field to recruit more diverse participants in a natural setting, or by simulating natural settings and interactions of the field in the lab. This workshop will showcase more naturalistic experimental paradigms, innovative tools and methods, and challenges in conducting research to optimize both internal and ecological validity.

  • Dominic DiFranzo, Cornell University
  • Natalie Bazarova, Cornell University
  • Shyam Sundar, Penn State University
  • Jeff Hancock, Stanford University

W13: The 3rd International Workshop on the Social Web for Environmental and Ecological Monitoring (SWEEM 2018)

The exponential growth of the popularity of social media has provided not only novel techniques for public communication and engagement, but has also generated unprecedented volumes of publicly-available, user-generated social media content. These trends open new opportunities for ecological and environmental applications, both in terms of alternative data sources and novel approaches for interacting with the public. The goal of the workshop is to bring together a combination of academic and industrial participants to discuss ideas, challenges, and solutions at the intersection of Social Media and Environmental/Ecological Science.

  • David J. Crandall, Indiana University Bloomington
  • Darian Frajberg, Politecnico di Milano

W15: The 3rd International Workshop on Event Analytics using Social Media Data (EASM)

Social media channels enjoy many advantages over traditional media channels, such as ubiquity, mobility, immediacy, and seamless communication in reporting, covering and sharing real-world events, e.g., the Boston bombings, the NBA finals, and the U.S Presidential elections. Given these advantages, social media posts such as tweets can typically reflect events as they happen, in real-time. Despite these benefits, social media channels also tend to be noisy, chaotic, and overwhelming. As a result, the vast amount of noisy social media data poses tremendous challenges for conducting in-depth analysis, which is critical to applications for event playback, journalistic investigation, storytelling, etc. We propose this workshop to provide a platform to understand the critical challenges in event analytics, determine the values they bring in various domains and to enable cross-fertilization of ideas between the different scientific (machine learning, data mining, social computing, NLP, etc) and functional (academia and business) groups.

  • Yuheng Hu, University of Illinois at Chicago
  • Yu-Ru Lin, University of Pittsburgh