Chirag Shah

TL;DR: A study to evaluate and predict the quality of an answer in a CQA setting and supports the argument that contextual information such as a user's profile, can be critical in evaluating and predicting content quality.

TL;DR: Algorithmic mediation improved both collaborative search (allowing a team of searchers to find relevant information more efficiently and effectively), and exploratory search (discovering relevant information that cannot be found while working individually).

TL;DR: The authors compared the agenda-setting cues of traditional media alongside those of online media in general and social media in particular, and found that people posting content to openly accessible social media outlets may be acting in response to mainstream news coverage, possibly as a "corrective" to perceived imbalances in that coverage, or whether such posts seem to have influenced professional media coverage of the issue.

TL;DR: The authors developed a research agenda for social Q&A, reviewing recent studies and identifying core issues, questions, and challenges, and identified core issues and challenges in social question and answer (Q&A).

TL;DR: This paper analyzes different groups of users according to their level of activity, and finds that bias exists in recommendation performance between different groups, and proposes a fairness constrained approach via heuristic re-ranking to mitigate this unfairness problem in the context of explainable recommendation over knowledge graphs.