Lying About Lying on Social Media: A Case Study of the 2019 Canadian Elections

King, Catherine; Bellutta, Daniele; Carley, Kathleen M.

doi:10.1007/978-3-030-61255-9_8

Cited by 5 publications

(5 citation statements)

References 7 publications

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“…Furthermore, while evidence is mixed regarding the impacts of bot activities during the pandemic (Himelein-Wachowiak et al, 2021; Xu & Sasahara, 2022), we found that in the online conversation on racism, bots’ greater salience triggered higher levels of hate speech over time. Contributing to the rich scholarship on bot-driven information operations during high-profile events like electoral contests for power (Ferrara et al, 2020; King et al, 2020; Woolley & Howard, 2016), evidence from this study thus illustrates how these activities do not abate during as disruptive a crisis like the COVID-19 pandemic but rather strategically assimilate their concerns in fueling emergent conflicts.…”

Section: Discussionmentioning

confidence: 82%

“…BotHunter has been trained on a variety of known bot datasets and shown to be competitive with state-of-the-art models (Beskow, 2020). Prior research has also successfully applied the BotHunter model across diverse settings to characterize bot-driven information operations (King et al, 2020; Moffitt et al, 2021; Uyheng et al, 2020). While bot activity is a diverse and evolving phenomenon (Ferrara et al, 2016), the training of BotHunter on diverse datasets of known information operations makes it particularly effective at detecting automated behavior aimed at amplifying particular narratives or disrupting online conversations (Beskow, 2020).…”

Section: Methodsmentioning

confidence: 99%

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Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

Uyheng

Bellutta

Carley

2022

Social Media + Society

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Online talk about racism has been salient throughout the COVID-19 pandemic. Yet while such social media conversations reflect existing tensions in the offline world, the same discourse has also become a target for information operations aiming to heighten social divisions. This article examines Twitter discussions of racism in the first and sixth months since COVID-19 was accorded pandemic status by the World Health Organization and uncovers dynamic associations with bot activity and hate speech. Humans initially constituted the most hateful accounts in online conversations about racism in March, but in August, bots dominated hate speech. Over time, greater bot activity likewise amplified levels of hate speech a week later. Moreover, while discourse about racism in March primarily featured an organic focus on racial identities like Asian and Chinese, we further observed a bot-dominated focus in August toward political identities like president, Democrat, and Republican. Although hate speech targeting Asian groups remained present among racism discussions in August, these findings suggest a bot-fueled redirection from focusing on racial groups at the onset of the pandemic to targeting politics closer to the 2020 US elections. This work enhances understanding of the complexity of racism discussions during the pandemic, its vulnerability to manipulation through information operations, and the large-scale quantitative study of inorganic hate campaigns in online social networks.

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Section: Discussionmentioning

confidence: 82%

Section: Methodsmentioning

confidence: 99%

Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

Uyheng

Bellutta

Carley

2022

Social Media + Society

Self Cite

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“…In China, for example, studies have shown that government relies on trolls to propagate certain perspective (Bolsover & Howard, 2018; King et al, 2020). These researchers believe manually created and disseminated propaganda is more effective strategy.…”

Section: Identifying Trolls and Botsmentioning

confidence: 99%

“…Trolls are paid professionals to run propaganda by setting up fake accounts on Twitter and Facebook to targeted propaganda and troll opposite groups. Alongside bots whose functionalities are comparatively limited, many researchers have analyzed the diverse nature of content generated by trolls King et al, 2020;Neyazi, 2019). In China, for example, studies have shown that government relies on trolls to propagate certain perspective (Bolsover & Howard, 2018;King et al, 2020).…”

Section: Identifying Trolls and Botsmentioning

confidence: 99%

“…Alongside bots whose functionalities are comparatively limited, many researchers have analyzed the diverse nature of content generated by trolls King et al, 2020;Neyazi, 2019). In China, for example, studies have shown that government relies on trolls to propagate certain perspective (Bolsover & Howard, 2018;King et al, 2020). These researchers believe manually created and disseminated propaganda is more effective strategy.…”

Section: Identifying Trolls and Botsmentioning

confidence: 99%

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Analyzing the State of Digital Information Warfare Between India and Pakistan on Twittersphere

2021

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In this study, we analyze the state of information warfare on Twittersphere between India and Pakistan in the wake of Pulwama attack in Kashmir region and the subsequent surgical strikes by Indian forces inside Pakistan. We selected two leading Twitter hashtags on the conflict from the two countries each. A total of 20,000 tweets were manually analyzed. Contrary to the existing scholarship on digital information warfare, we found citizens from both countries produced most of the content. Among the citizens, those Twitter handles that showed affiliations with the heads of governments that we consider as trolls were the leading contributors. Moreover, the study found that contributors from the two countries mainly posted on their own hashtags and did not engage in counter-arguments with the contributors from other country. This resulted in overwhelming support for the two countries in their own assorted hashtags and outright criticism in the hashtags originating from the other country.

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Computational Models for Social Good: Beyond Bias and Representation

Dancy

Joseph

2022

Lecture Notes in Computer Science

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Lying About Lying on Social Media: A Case Study of the 2019 Canadian Elections

Cited by 5 publications

References 7 publications

Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

Analyzing the State of Digital Information Warfare Between India and Pakistan on Twittersphere

Computational Models for Social Good: Beyond Bias and Representation

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