IDEAS home Printed from https://ideas.repec.org/a/spr/jcsosc/v8y2025i4d10.1007_s42001-025-00419-2.html
   My bibliography  Save this article

Understanding conversations on alcohol across diverse Reddit communities: a computational analysis

Author

Listed:
  • Mansi Shah

    (University of Texas at Austin)

  • Yara Acaf

    (University of Texas at Austin)

  • Michael Mackert

    (University of Texas at Austin)

Abstract

This study examines how diverse population segments within a U.S. state discuss alcohol-related issues on Reddit. Using computational methods, data were collected from three subreddits via the Reddit API. Textual and sentiment analyses were conducted on user comments, followed by machine learning techniques to identify frequently used words and topics. The results highlight distinct patterns across the subreddits. The findings underscore the cultural diversity within the same state and a sobriety-focused community. The insights have significant implications for tailoring statewide health communication campaigns. By addressing unique regional and cultural themes, campaigns can achieve greater relevance and effectiveness in reaching target audiences. This research highlights the value of leveraging social media data for nuanced, localized health communication strategies.

Suggested Citation

  • Mansi Shah & Yara Acaf & Michael Mackert, 2025. "Understanding conversations on alcohol across diverse Reddit communities: a computational analysis," Journal of Computational Social Science, Springer, vol. 8(4), pages 1-22, November.
    • Handle: RePEc:spr:jcsosc:v:8:y:2025:i:4:d:10.1007_s42001-025-00419-2
    DOI: 10.1007/s42001-025-00419-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42001-025-00419-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s42001-025-00419-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
    2. Audrey Redford & Angela K. Dills, 2021. "The political economy of drug and alcohol regulation during the COVID‐19 pandemic," Southern Economic Journal, John Wiley & Sons, vol. 87(4), pages 1175-1209, April.
    3. Isabel Martinez Leal & Matthew Taing & Virmarie Correa-Fernández & Ezemenari M. Obasi & Bryce Kyburz & Kathy Le & Litty Koshy & Tzuan A. Chen & Teresa Williams & Kathleen Casey & Daniel P. O’Connor & , 2021. "Addressing Smoking Cessation among Women in Substance Use Treatment: A Qualitative Approach to Guiding Tailored Interventions," IJERPH, MDPI, vol. 18(11), pages 1-25, May.
    4. Aditya Simha & Sana Ahmed & Ramakrishna Prasad & Akshay S. Dinesh & Arun Kandasamy & Naren P Rao, 2022. "Effect of national cultural dimensions and consumption rates on stigma toward alcohol and substance use disorders," International Journal of Social Psychiatry, , vol. 68(7), pages 1411-1417, November.
    5. Freimuth, V.S. & Quinn, S.C., 2004. "The contributions of health communication to eliminating health disparities," American Journal of Public Health, American Public Health Association, vol. 94(12), pages 2053-2055.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vincent Miozzi & Benjamin Powell, 2023. "The pre-pandemic political economy determinants of lockdown severity," Public Choice, Springer, vol. 197(1), pages 167-183, October.
    2. Maksym Polyakov & Morteza Chalak & Md. Sayed Iftekhar & Ram Pandit & Sorada Tapsuwan & Fan Zhang & Chunbo Ma, 2018. "Authorship, Collaboration, Topics, and Research Gaps in Environmental and Resource Economics 1991–2015," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 217-239, September.
    3. Baumgärtner, Martin & Zahner, Johannes, 2025. "Whatever it takes to understand a central banker — Embedding their words using neural networks," Journal of International Economics, Elsevier, vol. 157(C).
    4. Daoud, Adel & Kohl, Sebastian, 2016. "How much do sociologists write about economic topics? Using big data to test some conventional views in economic sociology, 1890 to 2014," MPIfG Discussion Paper 16/7, Max Planck Institute for the Study of Societies.
    5. Cardinale, Roberto & Cardinale, Ivano & Zupic, Ivan, 2024. "The EU's vulnerability to gas price and supply shocks: The role of mismatches between policy beliefs and changing international gas markets," Energy Economics, Elsevier, vol. 131(C).
    6. Shr-Wei Kao & Pin Luarn, 2020. "Topic Modeling Analysis of Social Enterprises: Twitter Evidence," Sustainability, MDPI, vol. 12(8), pages 1-20, April.
    7. Hsia-Ching Chang, 2016. "The Synergy of Scientometric Analysis and Knowledge Mapping with Topic Models: Modelling the Development Trajectories of Information Security and Cyber-Security Research," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-33, December.
    8. Susumu Nagayama & Hitoshi Mitsuhashi, 2022. "Explosive and implosive root concepts: An analysis of music moods rooted by two influential rap artists," PLOS ONE, Public Library of Science, vol. 17(7), pages 1-25, July.
    9. Holand, Øystein & Contiero, Barbara & Næss, Marius W. & Cozzi, Giulio, 2024. "“The Times They Are A-Changin' “ – research trends and perspectives of reindeer pastoralism – A review using text mining and topic modelling," Land Use Policy, Elsevier, vol. 136(C).
    10. Ozgun, Burcu & Broekel, Tom, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    11. Anita Mendiratta & Shveta Singh & Surendra Singh Yadav & Arvind Mahajan, 2023. "Bibliometric and Topic Modeling Analysis of Corporate Social Irresponsibility," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 319-339, September.
    12. Eric. W. K. See-To & Yang Yang, 2017. "Market sentiment dispersion and its effects on stock return and volatility," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 283-296, August.
    13. Lüdering Jochen & Winker Peter, 2016. "Forward or Backward Looking? The Economic Discourse and the Observed Reality," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(4), pages 483-515, August.
    14. Sabrina L. Woltmann & Lars Alkærsig, 2018. "Tracing university–industry knowledge transfer through a text mining approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 449-472, October.
    15. Alexander Brem & Petra A. Nylund & Saeed Roshani, 2024. "Unpacking the complexities of crisis innovation: a comprehensive review of ecosystem-level responses to exogenous shocks," Review of Managerial Science, Springer, vol. 18(8), pages 2441-2464, August.
    16. Motta Queiroz, Mariza & Roque, Carlos & Moura, Filipe & Marôco, João, 2024. "Understanding the expectations of parents regarding their children's school commuting by public transport using latent Dirichlet Allocation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    17. Prithwiraj Choudhury & Dan Wang & Natalie A. Carlson & Tarun Khanna, 2019. "Machine learning approaches to facial and text analysis: Discovering CEO oral communication styles," Strategic Management Journal, Wiley Blackwell, vol. 40(11), pages 1705-1732, November.
    18. Ulrich Fritsche & Johannes Puckelwald, 2018. "Deciphering Professional Forecasters’ Stories - Analyzing a Corpus of Textual Predictions for the German Economy," Macroeconomics and Finance Series 201804, University of Hamburg, Department of Socioeconomics.
    19. Domenica Fioredistella Iezzi & Angelica Spampinato & Andrea Volterrani, 2025. "Social media and multiple sclerosis: measuring narrations and Italian community users," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(4), pages 3703-3721, August.
    20. Nguyen Xuan Truong & Bui Hoang Ngoc & Nguyen Thai Ha, 2022. "The Impacts of Media Exposure on COVID-19 Preventive Behaviors Among Vietnamese People: Evidence Using Expanded Protection Motivation Theory," SAGE Open, , vol. 12(2), pages 21582440221, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcsosc:v:8:y:2025:i:4:d:10.1007_s42001-025-00419-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.