TY - JOUR

T1 - Bots Versus Humans

T2 - Discursive Activism During the Pandemic in the Iranian Twittersphere

AU - Kermani, Hossein

AU - Bayat Makou, Alireza

AU - Tafreshi, Amirali

AU - Mohamad Ghodsi, Amir

AU - Ataee, Homa

N1 - Funding Information: The first author thanks the Faculty of Social Sciences (University of Vienna) for supporting this study. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The first author has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 101029945.) This paper reflects only the authors’ views; the European Research Council Executive Agency is not responsible for any use that may be made of the information it contains.

PY - 2023/12/18

Y1 - 2023/12/18

N2 - This article explores how the pandemic in Iran was discursively framed by automated accounts and human users. While there is a growing body of literature on bot activism, little is known about how bots and humans framed the pandemic in authoritarian regimes. Drawing on networked framing theory, we use both computational and qualitative methods to fill this gap. Our empirical analysis centers on a data set of 4,165,177 tweets collected between 27 January 2020 and 18 April 2020. We found that while anti-regime human users strongly criticized Iran’s regime, pro-regime bots countered with messages emphasizing the sacrifices of medical staff, the strength of Iran, and the failings of Western governments in managing the crisis. Our results suggest that Persian Twitter human users were largely against the regime, while the regime employed bots extensively to maintain balance. Human users used sarcasm, while pro-regime bots invoked religious and revolutionary sentiments metaphorically to defend the regime. By focusing on a relatively unexplored context, this article adds to the growing literature on bot activism.

AB - This article explores how the pandemic in Iran was discursively framed by automated accounts and human users. While there is a growing body of literature on bot activism, little is known about how bots and humans framed the pandemic in authoritarian regimes. Drawing on networked framing theory, we use both computational and qualitative methods to fill this gap. Our empirical analysis centers on a data set of 4,165,177 tweets collected between 27 January 2020 and 18 April 2020. We found that while anti-regime human users strongly criticized Iran’s regime, pro-regime bots countered with messages emphasizing the sacrifices of medical staff, the strength of Iran, and the failings of Western governments in managing the crisis. Our results suggest that Persian Twitter human users were largely against the regime, while the regime employed bots extensively to maintain balance. Human users used sarcasm, while pro-regime bots invoked religious and revolutionary sentiments metaphorically to defend the regime. By focusing on a relatively unexplored context, this article adds to the growing literature on bot activism.

KW - bot activism

KW - Covid-19

KW - Iran

KW - networked framing

KW - Twitter

UR - http://www.scopus.com/inward/record.url?scp=85180198752&partnerID=8YFLogxK

U2 - 10.1177/20563051231216927

DO - 10.1177/20563051231216927

M3 - Article

AN - SCOPUS:85180198752

VL - 9

JO - Social Media and Society

JF - Social Media and Society

IS - 4

ER -