Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide

Research output: Working paperPreprintResearch

Standard

Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide. / Golovchenko, Yevgeniy; Stanczak, Karolina Ewa; Adler-Nissen, Rebecca; Wangen, Patrice; Augenstein, Isabelle.

arxiv.org, 2023.

Research output: Working paperPreprintResearch

Harvard

Golovchenko, Y, Stanczak, KE, Adler-Nissen, R, Wangen, P & Augenstein, I 2023 'Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide' arxiv.org.

APA

Golovchenko, Y., Stanczak, K. E., Adler-Nissen, R., Wangen, P., & Augenstein, I. (2023). Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide. arxiv.org.

Vancouver

Golovchenko Y, Stanczak KE, Adler-Nissen R, Wangen P, Augenstein I. Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide. arxiv.org. 2023.

Author

Golovchenko, Yevgeniy ; Stanczak, Karolina Ewa ; Adler-Nissen, Rebecca ; Wangen, Patrice ; Augenstein, Isabelle. / Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide. arxiv.org, 2023.

Bibtex

@techreport{4b06fb770f394705b501277a1ded09fb,
title = "Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide",
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.",
author = "Yevgeniy Golovchenko and Stanczak, {Karolina Ewa} and Rebecca Adler-Nissen and Patrice Wangen and Isabelle Augenstein",
year = "2023",
language = "English",
publisher = "arxiv.org",
type = "WorkingPaper",
institution = "arxiv.org",

}

RIS

TY - UNPB

T1 - Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide

AU - Golovchenko, Yevgeniy

AU - Stanczak, Karolina Ewa

AU - Adler-Nissen, Rebecca

AU - Wangen, Patrice

AU - Augenstein, Isabelle

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

M3 - Preprint

BT - Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide

PB - arxiv.org

ER -

ID: 383611846