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  1. Book ; Online: Invisible Women in Digital Diplomacy

    Golovchenko, Yevgeniy / Stańczak, Karolina / Adler-Nissen, Rebecca / Wangen, Patrice / Augenstein, Isabelle

    A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide

    2023  

    Abstract: Despite mounting evidence that women in foreign policy often bear the brunt of online hostility, the extent of online gender bias against diplomats remains unexplored. This paper offers the first global analysis of the treatment of women diplomats on ... ...

    Abstract Despite mounting evidence that women in foreign policy often bear the brunt of online hostility, the extent of online gender bias against diplomats remains unexplored. This paper offers the first global analysis of the treatment of women diplomats on social media. Introducing a multidimensional and multilingual methodology for studying online gender bias, it focuses on three critical elements: gendered language, negativity in tweets directed at diplomats, and the visibility of women diplomats. Our unique dataset encompasses ambassadors from 164 countries, their tweets, and the direct responses to these tweets in 65 different languages. Using automated content and sentiment analysis, our findings reveal a crucial gender bias. The language in responses to diplomatic tweets is only mildly gendered and largely pertains to international affairs and, generally, women ambassadors do not receive more negative reactions to their tweets than men, yet the pronounced discrepancy in online visibility stands out as a significant form of gender bias. Women receive a staggering 66.4% fewer retweets than men. By unraveling the invisibility that obscures women diplomats on social media, we hope to spark further research on online bias in international politics.
    Keywords Computer Science - Social and Information Networks ; Computer Science - Computers and Society
    Subject code 300
    Publishing date 2023-11-29
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Book ; Online: Mapping (Dis-)Information Flow about the MH17 Plane Crash

    Hartmann, Mareike / Golovchenko, Yevgeniy / Augenstein, Isabelle

    2019  

    Abstract: Digital media enables not only fast sharing of information, but also disinformation. One prominent case of an event leading to circulation of disinformation on social media is the MH17 plane crash. Studies analysing the spread of information about this ... ...

    Abstract Digital media enables not only fast sharing of information, but also disinformation. One prominent case of an event leading to circulation of disinformation on social media is the MH17 plane crash. Studies analysing the spread of information about this event on Twitter have focused on small, manually annotated datasets, or used proxys for data annotation. In this work, we examine to what extent text classifiers can be used to label data for subsequent content analysis, in particular we focus on predicting pro-Russian and pro-Ukrainian Twitter content related to the MH17 plane crash. Even though we find that a neural classifier improves over a hashtag based baseline, labeling pro-Russian and pro-Ukrainian content with high precision remains a challenging problem. We provide an error analysis underlining the difficulty of the task and identify factors that might help improve classification in future work. Finally, we show how the classifier can facilitate the annotation task for human annotators.
    Keywords Computer Science - Computation and Language ; Computer Science - Computers and Society
    Subject code 004
    Publishing date 2019-10-03
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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