The scale, reach, and real-time nature of the Internet is opening new frontiers for understanding the vulnerabilities in our societies, including inequalities and fragility in the face of a changing world. From tracking seasonal illnesses like the flu across countries and populations, to understanding the context of mental conditions such as anorexia and bulimia, web data has the potential to capture the struggles and wellbeing of diverse groups of people. Vulnerable populations including children, elderly, racial or ethnic minorities, socioeconomically disadvantaged, underinsured or those with certain medical conditions, are often absent in commonly used data sources. The recent developments around COVID-19 epidemic and many armed conflicts make these issues even more urgent, with an unequal share of both disease and economic burden among various populations. Further, we aim to spotlight the data and algorithmic biases, especially in the light of the recent generative AI models, to raise the awareness needed to build inclusive and fair systems when dealing with crisis management and vulnerable populations.

Thus, the aim of this workshop is to encourage the community to use new sources of data as well as methodologies to study the wellbeing of vulnerable populations. The selection of appropriate data sources, identification of vulnerable groups, and ethical considerations in the subsequent analysis are of great importance in the extension of the benefits of big data revolution to these populations. As such, the topic is highly multidisciplinary, bringing together researchers and practitioners in computer science, epidemiology, demography, linguistics, and many others.

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Topics of Interest

• Establishing cohorts, data de-biasing

• Validation via individual-level or aggregate-level data

• Linking data to disease and other well-being 

• Population data sources for validation

• Correlation analysis and other statistical methods

• Longitudinal analysis on social media

• Spatial, linguistic, and temporal analyses

• Privacy, ethics, and informed consent

• Biases and quality concerns around vulnerable groups in LLMs

• Data quality issues

Submission Guidelines

We invite submissions of technical papers and abstract proposals. 

• Technical papers should be up to 4 pages (short papers) or up to 8 pages (long papers). Technical papers must contain novel, previously-unpublished material related to the topics of the workshop. Accepted papers will be presented orally and will appear in the workshop proceedings.
• Abstract proposals must be up to 2 pages presenting an ongoing study, or a topic of discussion related to the workshop's topics of interest.

Papers must adhere to the ICWSM guidelines and be submitted through Easychair.

Publication

Long and Short papers will be published in ICWSM Workshop proceedings by the AAAI Press. Please follow the AAAI format.

Abstract proposals will not be published.

Committees

Program Committee

• Duilio Balsamo, Bocconi University

• Mike Conway, University of Utah

• Emilio Zagheni, Max Planck Institute for Demographic Research (MPIDR)

• Daniela Perrotta, Max Planck Institute for Demographic Research (MPIDR)

• Hernan Sarmiento, Universidad de Chile

• Ailbhe Finnerty, University College London (UCL)

• Mariano Beiro, Universidad de Buenos Aires

• Oscar Araque, Universidad Polit'ecnica de Madrid

• Vjosa Preniq, Queen Mary University London

• Derry Wijaya, Boston University

• Aleksandr Farseev, National University of Singapore

Organizing committee

• Kyriaki Kalimeri, ISI Foundation
• Yelena Mejova, ISI Foundation
• Daniela Paolotti, ISI Foundation

Contact

All questions about submissions should be emailed to Kyriaki Kalimeri kyriaki.kalimeri@isi.it and Yelena Mejova yelena.mejova@isi.it