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Developing Epidemiological Models with Differentiated Infected Intensity

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Social, Cultural, and Behavioral Modeling (SBP-BRiMS 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14972))

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Abstract

This study investigates the spread of toxic content on social media, a growing concern as online platforms serve as primary information sources. This research aims to enhance the accuracy of models capturing toxicity spread by differentiating between varying levels of toxicity intensity. Two epidemiological models are developed and assessed: the SEIRS model and a novel \(SEI_{m}I_{h}RS\) model. The latter divides infected users into moderate and highly infected groups to reflect the varying severity of toxic behavior. Both models are tested on six datasets to evaluate their performance. The \(SEI_{m}I_{h}RS\) model achieves even lower error rates, indicating a more precise representation of toxicity propagation. This research contributes a sophisticated tool for analyzing online toxicity, aiding policymakers and online platforms in developing targeted interventions and enhancing content moderation systems.

This research is funded in part by the U.S. National Science Foundation (OIA-1946391, OIA-1920920), U.S. Office of the Under Secretary of Defense for Research and Engineering (FA9550-22-1-0332), U.S. Army Research Office (W911NF-23-1-0011, W911NF-24-1-0078), U.S. Office of Naval Research (N00014-21-1-2121, N00014-21-1-2765, N00014-22-1-2318), U.S. Air Force Research Laboratory, U.S. Defense Advanced Research Projects Agency, Arkansas Research Alliance, the Jerry L. Maulden/Entergy Endowment at the University of Arkansas at Little Rock. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding organizations. The researchers gratefully acknowledge the support.

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Authors and Affiliations

  1. COSMOS Research Center, University of Arkansas - Little Rock, Little Rock, Arkansas, USA

    Niloofar Yousefi, Nitin Agarwal & Emmanuel Addai

Authors
  1. Niloofar Yousefi
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  2. Nitin Agarwal
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  3. Emmanuel Addai
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Corresponding author

Correspondence to Niloofar Yousefi .

Editor information

Editors and Affiliations

  1. United States Military Academy, Army Cyber Institute, West Point, NY, USA

    Robert Thomson

  2. The University of the Cumberlands, Williamsburg, KY, USA

    Aravind Hariharan

  3. Carnegie Mellon University, Pittsburgh, PA, USA

    Scott Renshaw

  4. Creighton University, Omaha, NE, USA

    Samer Al-khateeb

  5. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Annetta Burger

  6. Carnegie Mellon University, Pittsburg, PA, USA

    Patrick Park

  7. Army Cyber Institute, West Point, NY, USA

    Aryn Pyke

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Yousefi, N., Agarwal, N., Addai, E. (2024). Developing Epidemiological Models with Differentiated Infected Intensity. In: Thomson, R., et al. Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2024. Lecture Notes in Computer Science, vol 14972. Springer, Cham. https://doi.org/10.1007/978-3-031-72241-7_6

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  • DOI: https://doi.org/10.1007/978-3-031-72241-7_6

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