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Rissola_2022_Else_ipm
Journal article

Mental disorders on online social media through the lens of language and behaviour : analysis and visualisation

  • 2022
Published in:
  • Information processing & management. - 2022, vol. 59, no. 3, p. 102890
Social media mining
Mental health
Language analysis
Behaviour analysis
Information extraction
Visualisation
English Due to the worldwide accessibility to the Internet along with the continuous advances in mobile technologies, physical and digital worlds have become completely blended, and the proliferation of social media platforms has taken a leading role over this evolution. In this paper, we undertake a thorough analysis towards better visualising and understanding the factors that characterise and differentiate social media users affected by mental disorders. We perform different experiments studying multiple dimensions of language, including vocabulary uniqueness, word usage, linguistic style, psychometric attributes, emotions’ co-occurrence patterns, and online behavioural traits, including social engagement and posting trends. Our findings reveal significant differences on the use of function words, such as adverbs and verb tense, and topic-specific vocabulary, such as biological processes. As for emotional expression, we observe that affected users tend to share emotions more regularly than control individuals on average. Overall, the monthly posting variance of the affected groups is higher than the control groups. Moreover, we found evidence suggesting that language use on microblogging platforms is less distinguishable for users who have a mental disorder than other less restrictive platforms. In particular, we observe on Twitter less quantifiable differences between affected and control groups compared to Reddit.
Collections
Language
  • English
Classification
Computer science and technology
License
CC BY-NC-ND
Open access status
hybrid
Identifiers
Persistent URL
https://n2t.net/ark:/12658/srd1324936
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