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  1. Article ; Online: Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines.

    Uyheng, Joshua / Carley, Kathleen M

    Journal of computational social science

    2020  Volume 3, Issue 2, Page(s) 445–468

    Abstract: Online hate speech represents a serious problem exacerbated by the ongoing COVID-19 pandemic ... conversations about the pandemic in the United States and the Philippines. Our integrated analysis reveals ... denser and more isolated from others. We discuss several insights for probing issues of online hate ...

    Abstract Online hate speech represents a serious problem exacerbated by the ongoing COVID-19 pandemic. Although often anchored in real-world social divisions, hate speech in cyberspace may also be fueled inorganically by inauthentic actors like social bots. This work presents and employs a methodological pipeline for assessing the links between hate speech and bot-driven activity through the lens of social cybersecurity. Using a combination of machine learning and network science tools, we empirically characterize Twitter conversations about the pandemic in the United States and the Philippines. Our integrated analysis reveals idiosyncratic relationships between bots and hate speech across datasets, highlighting different network dynamics of racially charged toxicity in the US and political conflicts in the Philippines. Most crucially, we discover that bot activity is linked to higher hate in both countries, especially in communities which are denser and more isolated from others. We discuss several insights for probing issues of online hate speech and coordinated disinformation, especially through a global approach to computational social science.
    Keywords covid19
    Language English
    Publishing date 2020-10-20
    Publishing country Singapore
    Document type Journal Article
    ZDB-ID 2916161-7
    ISSN 2432-2725 ; 2432-2717
    ISSN (online) 2432-2725
    ISSN 2432-2717
    DOI 10.1007/s42001-020-00087-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines

    Uyheng, Joshua / Carley, Kathleen M

    J Comput Soc Sci

    Abstract: Online hate speech represents a serious problem exacerbated by the ongoing COVID-19 pandemic ... conversations about the pandemic in the United States and the Philippines. Our integrated analysis reveals ... denser and more isolated from others. We discuss several insights for probing issues of online hate ...

    Abstract Online hate speech represents a serious problem exacerbated by the ongoing COVID-19 pandemic. Although often anchored in real-world social divisions, hate speech in cyberspace may also be fueled inorganically by inauthentic actors like social bots. This work presents and employs a methodological pipeline for assessing the links between hate speech and bot-driven activity through the lens of social cybersecurity. Using a combination of machine learning and network science tools, we empirically characterize Twitter conversations about the pandemic in the United States and the Philippines. Our integrated analysis reveals idiosyncratic relationships between bots and hate speech across datasets, highlighting different network dynamics of racially charged toxicity in the US and political conflicts in the Philippines. Most crucially, we discover that bot activity is linked to higher hate in both countries, especially in communities which are denser and more isolated from others. We discuss several insights for probing issues of online hate speech and coordinated disinformation, especially through a global approach to computational social science.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #888325
    Database COVID19

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