arXiv AI By Nuhu Ibrahim, Riza Batista-Navarro

Automatic Detection of Deaths from Social Networking Sites

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arXiv:2608. 05183v1 Announce Type: cross Abstract: This dissertation analysed and discussed the differences in linguistic characteristics between pre-mortem and post-mortem social media content, and reported machine learning (ML) classifiers that achieved high performance in automatically detecting deaths of social networking site users from posts associated with their profiles.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning
Jun 10

AI Application Gives Users Real-Time Feedback on the Level of Peace in the Social Media Videos They Watch

arXiv:2601. 05232v3 Announce Type: replace-cross Abstract: Most people now get their news from videos on social media, such as YouTube and Facebook, rather than through curated journalism.

By P. Gilda (Columbia University), P. Dungarwal (Columbia University), A. Thongkham (Columbia University), E. T. Ajayi (St John's University), S. Choudhary (Columbia University), T. M. Terol (Columbia University), C. Lam (Columbia University), J. P. Araujo (Columbia University), M. McFadyen-Mungalln (Columbia University), L. S. Liebovitch (Columbia University), P. T. Coleman (Columbia University), H. West (Columbia University), K. Sieck (Toyota Research Institute), S. Carter (Toyota Research Institute)