Mental disorders on online social media through the lens of language and behaviour
analysis and visualisation
Informazioni aggiuntive
Autori
Ríssola E. A.,
Aliannejadi M.,
Crestani F.
Tipo
Articolo pubblicato in rivista scientifica
Anno
2022
Lingua
Inglese
Sommario
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.
Parole chiave
Social media mining, Mental health, Language analysis, Behaviour analysis, Information extraction, Visualisation
Periodico
Information processing & management
Volume
59
Numero ( Mese )
3
Pagine (o numero dell’articolo)
102890
Diffusione
Licenza
CC BY-NC-ND
Visibilità
Pubblico
Status open access
Hybrid
