Substance use and sentiment and topical tendencies: a study using social media conversations of youth experiencing homelessness

Guardat en:
Dades bibliogràfiques
Publicat a:Information Technology & People vol. 36, no. 6 (2023), p. 2515-2542
Autor principal: Deng, Tianjie
Altres autors: Barman-Adhikari, Anamika, Young Jin Lee, Dewri, Rinku, Bender, Kimberly
Publicat:
Emerald Group Publishing Limited
Matèries:
Accés en línia:Citation/Abstract
Full Text
Full Text - PDF
Etiquetes: Afegir etiqueta
Sense etiquetes, Sigues el primer a etiquetar aquest registre!

MARC

LEADER 00000nab a2200000uu 4500
001 2861046000
003 UK-CbPIL
022 |a 0959-3845 
022 |a 1758-5813 
022 |a 0167-5710 
024 7 |a 10.1108/ITP-12-2020-0860  |2 doi 
035 |a 2861046000 
045 2 |b d20230820  |b d20230930 
084 |a 14872  |2 nlm 
100 1 |a Deng, Tianjie  |u Department of Business Information and Analytics, Daniels College of Business, University of Denver, Denver, Colorado, USA 
245 1 |a Substance use and sentiment and topical tendencies: a study using social media conversations of youth experiencing homelessness 
260 |b Emerald Group Publishing Limited  |c 2023 
513 |a Journal Article 
520 3 |a PurposeThis study investigates associations between Facebook (FB) conversations and self-reports of substance use among youth experiencing homelessness (YEH). YEH engage in high rates of substance use and are often difficult to reach, for both research and interventions. Social media sites provide rich digital trace data for observing the social context of YEH's health behaviors. The authors aim to investigate the feasibility of using these big data and text mining techniques as a supplement to self-report surveys in detecting and understanding YEH attitudes and engagement in substance use.Design/methodology/approachParticipants took a self-report survey in addition to providing consent for researchers to download their Facebook feed data retrospectively. The authors collected survey responses from 92 participants and retrieved 33,204 textual Facebook conversations. The authors performed text mining analysis and statistical analysis including ANOVA and logistic regression to examine the relationship between YEH's Facebook conversations and their substance use.FindingsFacebook posts of YEH have a moderately positive sentiment. YEH substance users and non-users differed in their Facebook posts regarding: (1) overall sentiment and (2) topics discussed. Logistic regressions show that more positive sentiment in a respondent's FB conversation suggests a lower likelihood of marijuana usage. On the other hand, discussing money-related topics in the conversation increases YEH's likelihood of marijuana use.Originality/valueDigital trace data on social media sites represent a vast source of ecological data. This study demonstrates the feasibility of using such data from a hard-to-reach population to gain unique insights into YEH's health behaviors. The authors provide a text-mining-based toolkit for analyzing social media data for interpretation by experts from a variety of domains. 
653 |a Research 
653 |a Self report 
653 |a Big Data 
653 |a Social networks 
653 |a Drug abuse 
653 |a Health promotion 
653 |a Statistical analysis 
653 |a Feasibility studies 
653 |a Young adults 
653 |a Health behavior 
653 |a Human immunodeficiency virus--HIV 
653 |a Marijuana 
653 |a Data mining 
653 |a Feasibility 
653 |a Substance abuse 
653 |a Social environment 
653 |a Homeless people 
653 |a Social media 
653 |a Drug use 
653 |a Sexual health 
653 |a Victimization 
653 |a Natural language processing 
653 |a Mental health 
653 |a Polls & surveys 
653 |a Addictive behaviors 
653 |a Money 
653 |a Digital media 
653 |a Information technology 
653 |a Responses 
653 |a Quantitative analysis 
653 |a Mass media 
653 |a Youth 
653 |a Computer mediated communication 
653 |a Variance analysis 
653 |a Attitudes 
653 |a Writers 
653 |a Conversation 
700 1 |a Barman-Adhikari, Anamika  |u Graduate School of Social Work, University of Denver, Denver, Colorado, USA 
700 1 |a Young Jin Lee  |u Department of Business Information and Analytics, Daniels College of Business, University of Denver, Denver, Colorado, USA 
700 1 |a Dewri, Rinku  |u Department of Computer Science, University of Denver, Denver, Colorado, USA 
700 1 |a Bender, Kimberly  |u Graduate School of Social Work, University of Denver, Denver, Colorado, USA 
773 0 |t Information Technology & People  |g vol. 36, no. 6 (2023), p. 2515-2542 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2861046000/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/2861046000/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/2861046000/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch