South African bot behaviour post the July 2018 Twitter account cull

Featherstone, Coral

doi:10.1109/icabcd.2019.8851039

“…The similarity between these images is actually noticeable and interesting. Some scholars previously referred to social bots as "Twitter eggs" 42 and asserted that social bot accounts use the default profile photo of Twitter instead of using a picture (Featherstone, 2019;Forelle et al, 2015;Howard et al, 2016;Kollanyi et al, 2016).…”

Section: Social Bots and The Affordances Of Twittermentioning

confidence: 99%

Bot Politics: The Affordances of Twitter and Nonhuman Participation

Momeni

2024

Preprint

0

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Social networking sites have had an indisputable impact on the realm of political communications, increasing political discourses all around the world. Social media platforms offer some affordances that can be employed by users to facilitate their political activism. However, online political activism can be influenced by software robots which can interact on social media to emulate human users’ behaviour and influence their political opinion. This dissertation employs the theory of affordances and explores how the affordances of Twitter, including shareability, direct communication, dynamic interaction, searchability, and identifiability function in practice and have been used to facilitate the political engagement of human and nonhuman users. To do so, this dissertation uses the case study of the 2017 Women’s March in the United States to articulate the affordances of Twitter and explores how human users employ the affordances of this platform in their political engagement. The result of this analysis indicates that the affordances of Twitter such as shareability (tweeting, retweeting, hashtags), and dynamic interaction (liking) were the most prevalent affordances of this platform during the Women’s March. In addition, the case study of “building the wall” is used to analyze social bots’ function, behaviour, and interaction on Twitter, to demonstrate to what extend bots are capable of using the affordances of Twitter. This study demonstrates that bots use the affordance of shareability (retweeting) and dynamic interaction (liking) more than other affordances. However, this study did not find convincing evidence that these bots are able to generate new content, cultivate meaningful discussions, or directly provide responses to other tweets. The theory of affordances accredits two main components, the human and the environment, and claims that affordances are properties that the environment offers to any human who perceives and uses them. However, focusing on two main elements creates substantial limitations for employing the theory to explore artificial intelligence and self-improving machines. This study demonstrates that bots are capable of using some of the affordances of Twitter and imitate human-like performance to some degree. Therefore, by including a third component — nonhuman smart actors— this study proposes a new definition for the theory of affordances, which is a core contribution of this dissertation.

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“…The similarity between these images is actually noticeable and interesting. Some scholars previously referred to social bots as "Twitter eggs" 42 and asserted that social bot accounts use the default profile photo of Twitter instead of using a picture (Featherstone, 2019;Forelle et al, 2015;Howard et al, 2016;Kollanyi et al, 2016).…”

Section: Social Bots and The Affordances Of Twittermentioning

confidence: 99%

Bot Politics: The Affordances of Twitter and Nonhuman Participation

Momeni

2024

Preprint

0

View full text Add to dashboard Cite

Social networking sites have had an indisputable impact on the realm of political communications, increasing political discourses all around the world. Social media platforms offer some affordances that can be employed by users to facilitate their political activism. However, online political activism can be influenced by software robots which can interact on social media to emulate human users’ behaviour and influence their political opinion. This dissertation employs the theory of affordances and explores how the affordances of Twitter, including shareability, direct communication, dynamic interaction, searchability, and identifiability function in practice and have been used to facilitate the political engagement of human and nonhuman users. To do so, this dissertation uses the case study of the 2017 Women’s March in the United States to articulate the affordances of Twitter and explores how human users employ the affordances of this platform in their political engagement. The result of this analysis indicates that the affordances of Twitter such as shareability (tweeting, retweeting, hashtags), and dynamic interaction (liking) were the most prevalent affordances of this platform during the Women’s March. In addition, the case study of “building the wall” is used to analyze social bots’ function, behaviour, and interaction on Twitter, to demonstrate to what extend bots are capable of using the affordances of Twitter. This study demonstrates that bots use the affordance of shareability (retweeting) and dynamic interaction (liking) more than other affordances. However, this study did not find convincing evidence that these bots are able to generate new content, cultivate meaningful discussions, or directly provide responses to other tweets. The theory of affordances accredits two main components, the human and the environment, and claims that affordances are properties that the environment offers to any human who perceives and uses them. However, focusing on two main elements creates substantial limitations for employing the theory to explore artificial intelligence and self-improving machines. This study demonstrates that bots are capable of using some of the affordances of Twitter and imitate human-like performance to some degree. Therefore, by including a third component — nonhuman smart actors— this study proposes a new definition for the theory of affordances, which is a core contribution of this dissertation.

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“…The use of social network bots attracted particular public attention in South Africa when Bell Pottinger used social media to spread negative content. [23] Among the subscribers to the accounts of South African politicians there were bots that followed and moderated their tweets on their pages [24].…”

Section: Formation Of An Initial Data Setmentioning

confidence: 99%

An approach to identifying bots in social networks based on the special association of classifiers

Kuzmin¹,

Menisov²,

Shastun³

2020

Bus. Inform.

1

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Currently the use of bots, i.e. auto-accounts in social networks which are managed with special programs but disguised as ordinary users, has serious consequences. For example, bots have been used to influence political elections, distort information on the Internet and manipulate prices on the stock exchange. Many research teams concerned with the detection of such accounts have made use of machine learning methods. However, the practical results of detecting social network bots indicate significant limitations because the methodological tools used have language limitation and ineffective criteria for detection. This article presents improved countermeasures in a methodological approach to develop a universal social network account classifier for minimizing the average risk of errors in bot detection. The application of an assembly of classifiers united by a data adaptation criterion and results from the variance of each model found the formation of a universal classifier for social network accounts. The main results obtained by the authors consist of the criteria system and the categorical (nominal) features transformation approach for the formation of the special ensemble of classifiers. In practice, use of the ensemble of classifiers allows us to increase the effectiveness of bot detection compared to other approaches.

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South African bot behaviour post the July 2018 Twitter account cull

Cited by 3 publications

References 10 publications

Bot Politics: The Affordances of Twitter and Nonhuman Participation

Bot Politics: The Affordances of Twitter and Nonhuman Participation

Bot Politics: The Affordances of Twitter and Nonhuman Participation

An approach to identifying bots in social networks based on the special association of classifiers

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