Image credit: Mohammed Abed (AFP)

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.

We anticipate topics such as the below will be relevant:

• 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

See previous workshop webpages: 2019, 2021, 2022, 2023

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