Deep Dive into Anonymity: Large Scale Analysis of Quora Questions

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Abstract

Anonymity forms an integral and important part of our digital life. It enables us to express our true selves without the fear of judgment. In this paper, we investigate the different aspects of anonymity in the social Q&A site Quora. Quora allows users to explicitly post anonymous questions and such activity in this forum has become normative rather than a taboo. Through an analysis of millions of questions, we observe that at a global scale almost no difference manifests between the linguistic structure of the anonymous and the non-anonymous questions posted on Quora. We find that topical mixing at the global scale to be the primary reason for the absence. However, the differences start to feature once we “deep dive” and (topically) cluster the questions and compare them. In particular, we observe that the choice to post the question as anonymous is dependent on the user’s perception of anonymity and they often choose to speak about depression, anxiety, social ties and personal issues under the guise of anonymity. Subsequently, to gain further insights, we build an anonymity grid to identify the differences in the perception on anonymity of the user posting the question and the community of users answering it. We also look into the first response time of the questions and observe that it is lowest for topics which talk about personal and sensitive issues, which hints toward a higher degree of community support.

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Mathew, B., Dutt, R., Maity, S. K., Goyal, P., & Mukherjee, A. (2019). Deep Dive into Anonymity: Large Scale Analysis of Quora Questions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11864 LNCS, pp. 35–49). Springer. https://doi.org/10.1007/978-3-030-34971-4_3

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