arXiv subjects

Sonja Mei Wang

Publications and source records attributed to Sonja Mei Wang.

3 recordsLinked to original sources

arXiv2025

A Systematic Review of Echo Chamber Research: Comparative Analysis of Conceptualizations, Operationalizations, and Varying Outcomes

This systematic review synthesizes research on echo chambers and filter bubbles to explore the reasons behind dissent regarding their existence, antecedents, and effects. It provides a taxonomy of conceptualizations and operationalizations, analyzing how measurement approaches and contextual factors influence outcomes. The review of 129 studies identifies variations in measurement approaches, as well as regional, political, cultural, and platform-specific biases, as key factors contributing to the lack of consensus. Studies based on homophily and computational social science methods often support the echo chamber hypothesis, while research on content exposure and broader media environments, such as surveys, tends to challenge it. Group behavior, cultural influences, instant messaging platforms, and short video platforms remain underexplored. The strong geographic focus on the United States further highlights the need for studies in multi-party systems and regions beyond the Global North. Future research should prioritize cross-platform studies, continuous algorithmic audits, and investigations into the causal links between polarization, fragmentation, and echo chambers to advance the field. This review also provides recommendations for using the EUs Digital Services Act to enhance research in this area and conduct studies outside the US in multi-party systems. By addressing these gaps, this review contributes to a more comprehensive understanding of echo chambers, their measurement, and their societal impacts.

cs.SI↗

arXiv2024

OneLove beyond the field -- A few-shot pipeline for topic and sentiment analysis during the FIFA World Cup in Qatar

The FIFA World Cup in Qatar was discussed extensively in the news and on social media. Due to news reports with allegations of human rights violations, there were calls to boycott it. Wearing a OneLove armband was part of a planned protest activity. Controversy around the armband arose when FIFA threatened to sanction captains who wear it. To understand what topics Twitter users Tweeted about and what the opinion of German Twitter users was towards the OneLove armband, we performed an analysis of German Tweets published during the World Cup using in-context learning with LLMs. We validated the labels on human annotations. We found that Twitter users initially discussed the armband's impact, LGBT rights, and politics; after the ban, the conversation shifted towards politics in sports in general, accompanied by a subtle shift in sentiment towards neutrality. Our evaluation serves as a framework for future research to explore the impact of sports activism and evolving public sentiment. This is especially useful in settings where labeling datasets for specific opinions is unfeasible, such as when events are unfolding.

cs.CL↗

arXiv2022

Documenting Data Production Processes: A Participatory Approach for Data Work

The opacity of machine learning data is a significant threat to ethical data work and intelligible systems. Previous research has addressed this issue by proposing standardized checklists to document datasets. This paper expands that field of inquiry by proposing a shift of perspective: from documenting datasets toward documenting data production. We draw on participatory design and collaborate with data workers at two companies located in Bulgaria and Argentina, where the collection and annotation of data for machine learning are outsourced. Our investigation comprises 2.5 years of research, including 33 semi-structured interviews, five co-design workshops, the development of prototypes, and several feedback instances with participants. We identify key challenges and requirements related to the integration of documentation practices in real-world data production scenarios. Our findings comprise important design considerations and highlight the value of designing data documentation based on the needs of data workers. We argue that a view of documentation as a boundary object, i.e., an object that can be used differently across organizations and teams but holds enough immutable content to maintain integrity, can be useful when designing documentation to retrieve heterogeneous, often distributed, contexts of data production.

cs.HC↗