output
20072026
most citedPublic discourse and sentiment during the COVID-19 pandemic: using Latent Dirichlet Allocation for topic modeling on Twitter

360 citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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cs.SI2020★ 360 cited

Public discourse and sentiment during the COVID-19 pandemic: using Latent Dirichlet Allocation for topic modeling on Twitter

Jia Xue, Junxiang Chen, Chen Chen +3

The study aims to understand Twitter users' discourse and psychological reactions to COVID-19. We use machine learning techniques to analyze about 1.9 million Tweets (written in En…

cs.SI2015★ 1 cited

Recognizing Temporal Linguistic Expression Pattern of Individual with Suicide Risk on Social Media

Aiqi Zhang, Ang Li, Tingshao Zhu

Suicide is a global public health problem. Early detection of individual suicide risk plays a key role in suicide prevention. In this paper, we propose to look into individual suic…