#suicidal - A multipronged approach to identify and explore suicidal ideation in twitter

Pradyumna Prakhar Sinha, Debanjan Mahata, Rohan Mishra, Rajiv Ratn Shah, Ramit Sawhney, Huan Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Technological advancements have led to the creation of social media platforms like Twitter, where people have started voicing their views over rarely discussed and socially stigmatizing issues. Twitter, is increasingly being used for studying psycho-linguistic phenomenon spanning from expressions of adverse drug reactions, depressions, to suicidality. In this work we focus on identifying suicidal posts from Twitter. Towards this objective we take a multipronged approach and implement different neural network models such as sequential models and graph convolutional networks, that are trained on textual content shared in Twitter, the historical tweeting activity of the users and social network formed between different users posting about suicidality. We train a stacked ensemble of classifiers representing different aspects of suicidal tweeting activity, and achieve state-of-the-art results on a new manually annotated dataset developed by us, that contains textual as well as network information of suicidal tweets. We further investigate into the trained models and perform qualitative analysis showing how historical tweeting activity and rich information embedded in the homophily networks amongst users in Twitter, aids in accurately identifying tweets expressing suicidal intent.

Original languageEnglish (US)
Title of host publicationCIKM 2019 - Proceedings of the 28th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages941-950
Number of pages10
ISBN (Electronic)9781450369763
DOIs
StatePublished - Nov 3 2019
Externally publishedYes
Event28th ACM International Conference on Information and Knowledge Management, CIKM 2019 - Beijing, China
Duration: Nov 3 2019Nov 7 2019

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference28th ACM International Conference on Information and Knowledge Management, CIKM 2019
CountryChina
CityBeijing
Period11/3/1911/7/19

Keywords

  • Health informatics
  • Social media mining
  • Suicidal ideation

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

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  • Cite this

    Sinha, P. P., Mahata, D., Mishra, R., Shah, R. R., Sawhney, R., & Liu, H. (2019). #suicidal - A multipronged approach to identify and explore suicidal ideation in twitter. In CIKM 2019 - Proceedings of the 28th ACM International Conference on Information and Knowledge Management (pp. 941-950). (International Conference on Information and Knowledge Management, Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3357384.3358060