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Exploring the Prediction of Personality Traits from Drug Consumption Profiles
Jönköping University, Tekniska Högskolan, JTH, Datateknik och informatik.ORCID-id: 0000-0003-4344-9986
Faculty of Mathematics, Natural Sciences and Information, Technologies (FAMNIT), University of Primorska, Koper, Slovenia.
2020 (Engelska)Ingår i: Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery (ACM), 2020, s. 2-5Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The number of people that have been in touch with drugs is continuously increasing. Excessive intake of drugs becomes problematic when it turns into disorderly behaviors, such as addictions. In order to treat these disorderly behaviors, treatment plans often adhere to a one-size-fits-all approach with fixed and standardized steps. However, for effective treatment of disorderly behaviors it has been acknowledged that personalized treatment programs are necessary. The personality of people has been argued to be a factor that plays an important role in setting up effective treatment plans. In this work we explored the predictability of people’s personality traits based on their drug consumption profile. Based on self-reported consumption frequencies of "abusable psychoactive drugs," we found among 1878 respondents that drug consumption profiles can be used to predict people’s personality traits. The prediction of personality traits can be used to circumvent intruding questionnaires and to implicitly create personalized treatment programs.

Ort, förlag, år, upplaga, sidor
Association for Computing Machinery (ACM), 2020. s. 2-5
Nyckelord [en]
disorderly behaviors, personalized treatment plans, user modeling, drug consumption, addiction, personality
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:hj:diva-50067DOI: 10.1145/3386392.3397589ISBN: 978-1-4503-7950-2 (digital)OAI: oai:DiVA.org:hj-50067DiVA, id: diva2:1454181
Konferens
UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization, Genoa, Italy, 12-18 July, 2020
Tillgänglig från: 2020-07-15 Skapad: 2020-07-15 Senast uppdaterad: 2025-10-13Bibliografiskt granskad

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