Biography
Eszter Hargittai is Professor and holds the Chair of Internet Use and Society at the Department of Communication and Media Research of the University of Zurich (UZH). She is a Fellow of the International Communication Association and an External Member of the Hungarian Academy of Sciences. She received her Ph.D. in Sociology from Princeton University and her BA in Sociology from Smith College. Prior to joining UZH, she was the Delaney Family Professor of Communication Studies at Northwestern University.

Keynote: Older adults are more tech savvy than you think: implications for your research agenda
(Thursday, May 23; 14:00-15:00)
Adults 60 and over make up an increasing portion of the population yet they are often excluded from studies of Internet use. This talk draws on national survey data to show how older adults compare to younger age groups in their Internet uses and skills. Findings show that many older adults are more savvy and more active than popular rhetoric would suggest, including on social media where their engagement is sometimes close to those of younger cohorts. The talk highlights the importance of including a varied population group in studies that make generalizable claims.

Biography
Jie Tang is a WeBank Chair Professor of the Department of Computer Science at Tsinghua University. He is a Fellow of the ACM, a Fellow of AAAI, and a Fellow of IEEE. His interests include artificial general intelligence, data mining, social networks, and machine learning. He served as General Co-Chair of WWW’23, and PC Co-Chair of WWW’21, CIKM’16, WSDM’15, and EiC of IEEE T. on Big Data and AI Open J. He is leading several major efforts on building large language models in China. He also invented AMiner.cn, which has attracted 30 million users from 220 countries/regions in the world. He was honored with the SIGKDD Test-of-Time Award, the 2nd National Award for Science&Technology, NSFC for Distinguished Young Scholar, and SIGKDD Service Award.

Keynote: The ChatGLM’s Road to AGI
(Friday, May 24; 09:00-10:00)
Large language models have substantially advanced the state of the art in various AI tasks, such as natural language understanding and text generation, and image processing, multimodal modeling. In this talk, we will first introduce the development of AI in the past decades, in particular from the angle of China. We will also talk about the opportunities, challenges, and risks of AGI in the future. In the second part of the talk, we will use ChatGLM, an alternative but open-sourced model to ChatGPT, as an example to explain our understanding and insights derived during the implementation of the model.

Biography
Dirk Hovy is a professor in the computing sciences department at Bocconi University in Milan, Italy. He is also the scientific director of the Data and Marketing insights research unit. Before that, he was faculty and postdoc in Copenhagen, got a PhD in NLP from USC, and a master’s degree in linguistics from Marburg, Germany. He is interested in the interaction between language, society, and machine learning, or what language can tell us about society and what computers can tell us about language. He has authored over 100 articles on these topics, including three best paper awards. He is also the author of two textbooks on using text analysis in Python for social science research (https://bit.ly/3dhaEQ7 and https://bit.ly/3sYiwMH). Dirk has organized one conference and several workshops (on abusive language, ethics in NLP, and computational social science and sociolinguistics). 

Abstract
(Friday, May 24; 14:00-15:00)
T.B.D.

Biography
Hannes Werthner is a retired Computer Science Professor at the TU Wien, Austria, where he also served as the Dean of the faculty of Informatics. Prior to joining TU Wien, he had professorships at Austrian and international Universities. His research is in fields such as Decision Support Systems, E-Commerce and Recommender Systems. Besides research and teaching he founded several initiatives such as the Vienna PhD School of Informatics or the i2c / Informatics Innovation Center. He carefully observes how computer science and information technology are changing the world and us. This is his motivation for Digital Humanism, whose Vienna Manifesto he initiated in 2019. Since then he is active in this field – see also his latest contribution: “Introduction to Digital Humanism” (link.springer.com/book/10.1007/978-3-031-45304-5)

Keynote: Digital Humanism
(Wednesday, May 22; 14:00-15:00)
Information Technology changes ourselves and the world, from the individual level up to the ongoing geo-political powerplay. From an ontological point of view, it influences how we perceive the world and how we think about it. This transformation process took place in an extremely short period of time, at a very high speed. We highlight some features of this process, which, besides its enormous achievements, shows also serious shortcomings. The question posed is not a simple one: IT (including AI) may help solve the world’s multiple crises and make it a better place, but at the same time it is part of the problem (some even see it as the cause). We understand Digital Humanism as an answer to this question, as an approach to developing and regulating digital technologies so that they are used for the benefit of people and nature. It is a proactive approach that focuses on the integration of technical and social innovation.

Biography
Jennifer Pan is a political scientist whose research focuses on political communication, digital media, and authoritarian politics. She is the Sir Robert Ho Tung Professor of Chinese Studies, Professor of Communication and (by courtesy) Political Science and Sociology, and a Senior Fellow at the Freeman Spogli Institute for International Studies at Stanford University. Dr. Pan’s research uses experimental and computational methods with large-scale datasets on political activity to answer questions about the role of digital media in authoritarian and democratic politics, including how political censorship, propaganda, and information manipulation work in the digital age and how preferences and behaviors are shaped as a result.

Keynote: China in the Global Information Ecosystem
(Wednesday, May 22; 09:00-10:00)
While digital communication technologies have revolutionized the way information can flow across borders and national boundaries, information does not flow freely everywhere. Governments around the world impose restrictions on access to digital information, and nowhere is the effort to control the transnational flow of digital information more extensive and sustained than in China. This talk will highlight empirical findings on how information flows between China and the global information ecosystem.

Web Science studies a highly complex socio-technical environment. Visualisation is a common form of representation for data. This workshop raises questions about sonification for Web Science data. Drawing from both ideas of representation and reflexively using computational models, the workshop will provoke questions about how to design models and listening. The aim is to develop a community drawing from existing models and to create or identify a set of resources that can be developed to support future research.

• Iain Emsley (iain.emsley@warwick.ac.uk)
  Centre for Interdisciplinary Methodologies, University of Warwick, Coventry, UK
• David De Roure (david.deroure@oerc.ox.ac.uk)
  Oxford eResearch Centre, University of Oxford, Oxford, UK
  

The workshop aims to address the challenges and opportunities in public opinion research at the intersection of traditional survey data and social media data. Acknowledging the limitations of both data sources, such as biases in survey responses and issues of representativeness in social media data, the workshop seeks to explore the integration of these datasets using AI methodologies. This scholarly endeavor, led by international experts, will feature abstract submissions, keynote addresses, and paper presentations focusing on innovative strategies, ethical considerations, and practical applications in Computational Social Science (CSS). The event targets an academic audience, emphasizing the importance of integrating surveys and social media data to advance public opinion research and contribute to the academic discipline.

• Mehmet Fuat Kına (mkina18@ku.edu.tr)
  Center for Computational Social Sciences, Koç University
• Şükrü Atsızelti (satsizelti22@ku.edu.tr)
  Sociology Department, Koç University
• Oğuz Gürerk, Researcher (oguzgurerk@gmail.com)
  Center for Computational Social Sciences, Koç University
• Erdem Yörük (eryoruk@ku.edu.tr)
  Center for Computational Social Sciences and Sociology Department, Koç University
• Ali Hürriyetoğlu (ahurriyetoglu@ku.edu.tr)
  KNAW Humanities Cluster DHLab

In December 2023, the .au Domain Administration published an Atlas of Australia Online which combines .au registry data with publicly available geographic, economic and technical data to depict the Australian digital landscape.
Using a new method to collate, rank and cluster .au domain names, the research applies machine learning to map the Australian technology landscape to identify areas of high digital business intensity and clusters of technological innovation.
This workshop / tutorial is designed to share the methodology and insights from this policy focused research report as an example of interdisciplinary research into the impact of the Web in society. Since this research focuses on the relationship between the domain registry record and geographic, economic and technical data it provides a unique perspective on the landscape of the Web in Australia. Some of the insights revealed may be relevant in other jurisdictions, and there are opportunities to extend this research into new avenues.
The research report can be downloaded here: https://www.auda.org.au/news-events-insights/reporting/research-reports/atlas-australia-online-2023

• Claire McFarland (claire.mcfarland@gmail.com)
  Director, Beesness Consulting University of Technology, Sydney, NSW, Australia
• Professor Paul McCarthy (paul@leagueofscholars.com)
  CEO, League of Scholars Adjunct Professor of Computer Science, UNSW Sydney, Australia
• Michael Lewis (michael.lewis@auda.org.au)
  Manager, Industry Relations .au Domain Administration Melbourne, VIC, Australia

With the advancement of digital technologies and gadgets, online content is easily accessible. At the same time, harmful content also gets spread. There are different harmful content available on different platforms in multiple languages. The topic of harmful content is broad and covers multiple research directions. But from the user’s aspect, they are affected by them all. Often, it is studied individually, like misinformation and hate speech. Research has been done on one platform, monolingual, on a particular issue. It leads to harmful content spreaders switching platforms and languages to reach the user base. Harmful is not limited to social media but also news media. Spreader shares harmful content in posts, news articles, comments, and hyperlinks. So, there is a need to study the harmful content by combining cross-platform, language and topics.
Hence, by proposing the workshop, we plan to bring the research on harmful content under one umbrella so that research on different topics can bring some novel methods and recommendations for users. The workshop will cover the ongoing issue of war or elections in 2024. We propose a workshop, DOHW: Diffusion of Harmful Content on Online Web, which brings together the research on different topics of harmful content. We expect to discuss good research work and future research directions.

Workshop Website: https://dhow-workshop.github.io/

• Thomas Mandl
  University of Hildesheim, Germany
• Haiming Liu
  University of Southampton, United Kingdom
• Gautam Kishore Shahi (gautamshahi16@gmail.com)
  University of Duisburg-Essen, Germany
• Amit Kumar Jaiswal
  University of Surrey, United Kingdom
• Luis-Daniel Ibáñez
  University of Southampton, United Kingdom
• Durgesh Nandini
  University of Bayreuth, Germany

Clustering is a fundamental problem in data science, aiming to group objects based on similarity. Among existing options in the literature, correlation clustering stands out for its ability to group similar objects together while ensuring dissimilar ones are placed in separate clusters. This method finds applicability across diverse data types, such as relational and graph data, including Online Social Networks (OSNs). However, the potential of correlation clustering in addressing critical challenges like fair clustering and uncovering polarized communities in OSNs lacks a comprehensive exploration. Fair clustering addresses biases in algorithmic data analysis, crucial in grouping OSN users in clusters that are not dominated by a
specific type of sensitive data class (e.g., people having the same sex). Instead, detecting polarized communities reveals groups of users driven by divergent ideologies, essential in understanding online discourse dynamics. This tutorial aims to comprehensively explore correlation clustering’s versatility in tackling relevant societal challenges within online communities, such as fair clustering and uncovering polarized communities in OSNs.

• Domenico Mandaglio (d.mandaglio@dimes.unical.it)
  DIMES Dept., University of Calabria Rende (CS), Italy
• Lucio La Cava (lucio.lacava@dimes.unical.it)
  DIMES Dept., University of Calabria Rende (CS), Italy
• Andrea Tagarelli (andrea.tagarelli@unical.it)
  DIMES Dept., University of Calabria Rende (CS), Italy

Where:
Alte Kanzlei Stuttgart GmbH
Schillerplatz 5
70173 Stuttgart