Web-based technologies have proven to be playing a vital role in enabling us to cope with the global pandemic. Having experienced two years of “crisis,” many new norms have been forming, both socially and technologically. While some people long to return to how things were before the pandemic, others are questioning whether that is a state worth returning to. The main theme of this year’s conference, therefore, is the old vs. the new normal. Even though the conference accepts a wide range of topics (see below), papers discussing this overall issue would be particularly welcomed. 

Web Science is an interdisciplinary field dedicated to understanding the complex and multiple impacts of the Web on society, and vice versa. As such, the field of Web Science is particularly well situated to address pressing issues of our time. 

Methodologically, Web Science is a discipline that is agnostic to specific methods. We welcome quantitative, qualitative and mixed methods research, including methods from the social sciences and computer science. In addition, we welcome work that explores the ethics of Web-based data collection and research and those which have a broader perspective on the Web and that combine analyses of Web data and other types of data (e.g., from surveys or interviews) to better understand user behaviour (i.e., online and offline).

Building on our theme for 2022, we especially welcome contributions on:

    Successful cases of interdisciplinary and cross-disciplinary Web research
    Trends in globalisation, fragmentation, rejoining, and Balkanisation of the Web
    Automation and AI in all its manifestations relevant to the Web
    Interrogate questions of discrimination, representation and fairness
    Bring lenses such as intersectionality or design justice to questions of marginalisation and inequality
    Ethical challenges of technologies, data, algorithms, platforms, and people in the Web
    Modeling Web-related structures, data, users and behaviours
    Impact of AI and machine learning on the development of Web Science
    Detecting, preventing and predicting anomalies in Web data (e.g., fake content, spam, algorithmic and data biases)
    Data curation, Web archives and stewardship in Web Science
    Safeguarding and governance of the Web, including anonymity, security and trust
    Temporal and spatial dimensions of the Web as a repository of information
    The architecture and philosophy of the Web
    Social machines, crowd computing and collective intelligence
    Analysis and modeling of human vs. automatic behaviour (e.g., bots) and their influence on the structure of the Web and responding behaviour
    Critical analyses of the Web and Web technologies 
    Web economics, social entrepreneurship, and innovation
    Analysis of online social and information networks
    Legal issues including rights and accountability for AI actors
    Humanities, arts, and culture on the Web
    Inclusion, literacy and the digital divide
    Politics and social activism on the Web
    Online education and remote learning
    Health and well-being online