Suicide Ideation Detection on Social Media During COVID-19 via Adversarial and Multi-task Learning

Jun Li, Zhihan Yan, Zehang Lin, Xingyun Liu, Hong Va Leong, Nancy Xiaonan Yu, Qing Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Suicide ideation detection on social media is a challenging problem due to its implicitness. In this paper, we present an approach to detect suicide ideation on social media based on a BERT-LSTM model with Adversarial and Multi-task learning (BLAM). More specifically, BLAM combines BERT model with Bi-LSTM model to extract deeper and richer features. Furthermore, emotion classification is utilized as an auxiliary task to perform multi-task learning, which enriches the extracted features with emotion information that enhances the identification of suicide. In addition, BLAM generates adversarial noise by adversarial learning improving the generalization ability of the model. Extensive experiments conducted on our collected Suicide Ideation Detection (SID) dataset demonstrate the competitive superiority of BLAM compared with the state-of-the-art methods.

Original languageEnglish
Title of host publicationWeb and Big Data - 5th International Joint Conference, APWeb-WAIM 2021, Proceedings
EditorsLeong Hou U, Marc Spaniol, Yasushi Sakurai, Junying Chen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages140-145
Number of pages6
ISBN (Print)9783030858957
DOIs
Publication statusPublished - 2021
Event5th International Joint Conference on Asia-Pacific Web and Web-Age Information Management, APWeb-WAIM 2021 - Guangzhou, China
Duration: 23 Aug 202125 Aug 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12858 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Joint Conference on Asia-Pacific Web and Web-Age Information Management, APWeb-WAIM 2021
Country/TerritoryChina
CityGuangzhou
Period23/08/2125/08/21

Keywords

  • Adversarial learning
  • Multi-task learning
  • Suicide ideation detection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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