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New Approaches to Extract Information From Posts on COVID-19 Published on Reddit

Author

Listed:
  • Gianluca Bonifazi

    (Department of Information Engineering, Polytechnic University of Marche, 60131, Ancona, Via Brecce Bianche 12, Italy)

  • Enrico Corradini

    (Department of Information Engineering, Polytechnic University of Marche, 60131, Ancona, Via Brecce Bianche 12, Italy)

  • Domenico Ursino

    (Department of Information Engineering, Polytechnic University of Marche, 60131, Ancona, Via Brecce Bianche 12, Italy)

  • Luca Virgili

    (Department of Information Engineering, Polytechnic University of Marche, 60131, Ancona, Via Brecce Bianche 12, Italy)

Abstract

In the last two years, we have seen a huge number of debates and discussions on COVID-19 in social media. Many authors have analyzed these debates on Facebook and Twitter, while very few ones have considered Reddit. In this paper, we focus on this social network and propose three approaches to extract information from posts on COVID-19 published in it. The first performs a semi-automatic and dynamic classification of Reddit posts. The second automatically constructs virtual subreddits, each characterized by homogeneous themes. The third automatically identifies virtual communities of users with homogeneous themes. The three approaches represent an advance over the past literature. In fact, the latter lacks studies regarding classification algorithms capable of outlining the differences among the thousands of posts on COVID-19 in Reddit. Analogously, it lacks approaches able to build virtual subreddits with homogeneous topics or virtual communities of users with common interests.

Suggested Citation

  • Gianluca Bonifazi & Enrico Corradini & Domenico Ursino & Luca Virgili, 2022. "New Approaches to Extract Information From Posts on COVID-19 Published on Reddit," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 21(05), pages 1385-1431, September.
    • Handle: RePEc:wsi:ijitdm:v:21:y:2022:i:05:n:s0219622022500213
    DOI: 10.1142/S0219622022500213
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    Cited by:

    1. Naythan Villafuerte & Santiago Manzano & Paulina Ayala & Marcelo V. García, 2023. "Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device," Future Internet, MDPI, vol. 15(7), pages 1-29, June.
    2. Carlos Henríquez Miranda & German Sanchez-Torres & Dixon Salcedo, 2023. "Exploring the Evolution of Sentiment in Spanish Pandemic Tweets: A Data Analysis Based on a Fine-Tuned BERT Architecture," Data, MDPI, vol. 8(6), pages 1-18, May.

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