Mapping Intersections of Politics and Information in Twenty-First-Century Cyberculture

Wheeler, Maurice B.; Muwanguzi, Samuel

doi:10.1086/717231

Cited by 2 publications

(2 citation statements)

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“…Such strategies are part of a broader trend of incivility by American politicians on Twitter, with uncivil tweets serving as powerful means of political mobilization and fundraising ( Ballard et al, 2022 ) by drawing on emotions such as anger ( Joosse & Zelinsky, 2022 ; Bernecker, Wenzler & Sassenberg, 2019 ); the ensuing attention may even lead politicians to engage into greater incivility ( Frimer et al, 2022 ). In the case of Trump, the violence-inducing rhetoric resulted in permanent suspension of his Twitter account, days before being charged by the House of Representatives for “incitement of insurrection” ( Wheeler & Muwanguzi, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

(Re)shaping online narratives: when bots promote the message of President Trump during his first impeachment

Galgoczy

Phatak

Vinson

et al. 2022

PeerJ Computer Science

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Influencing and framing debates on Twitter provides power to shape public opinion. Bots have become essential tools of ‘computational propaganda’ on social media such as Twitter, often contributing to a large fraction of the tweets regarding political events such as elections. Although analyses have been conducted regarding the first impeachment of former president Donald Trump, they have been focused on either a manual examination of relatively few tweets to emphasize rhetoric, or the use of Natural Language Processing (NLP) of a much larger corpus with respect to common metrics such as sentiment. In this paper, we complement existing analyses by examining the role of bots in the first impeachment with respect to three questions as follows. (Q1) Are bots actively involved in the debate? (Q2) Do bots target one political affiliation more than another? (Q3) Which sources are used by bots to support their arguments? Our methods start with collecting over 13M tweets on six key dates, from October 6th 2019 to January 21st 2020. We used machine learning to evaluate the sentiment of the tweets (via BERT) and whether it originates from a bot. We then examined these sentiments with respect to a balanced sample of Democrats and Republicans directly relevant to the impeachment, such as House Speaker Nancy Pelosi, senator Mitch McConnell, and (then former Vice President) Joe Biden. The content of posts from bots was further analyzed with respect to the sources used (with bias ratings from AllSides and Ad Fontes) and themes. Our first finding is that bots have played a significant role in contributing to the overall negative tone of the debate (Q1). Bots were targeting Democrats more than Republicans (Q2), as evidenced both by a difference in ratio (bots had more negative-to-positive tweets on Democrats than Republicans) and in composition (use of derogatory nicknames). Finally, the sources provided by bots were almost twice as likely to be from the right than the left, with a noticeable use of hyper-partisan right and most extreme right sources (Q3). Bots were thus purposely used to promote a misleading version of events. Overall, this suggests an intentional use of bots as part of a strategy, thus providing further confirmation that computational propaganda is involved in defining political events in the United States. As any empirical analysis, our work has several limitations. For example, Trump’s rhetoric on Twitter has previously been characterized by an overly negative tone, thus tweets detected as negative may be echoing his message rather than acting against him. Previous works show that this possibility is limited, and its existence would only strengthen our conclusions. As our analysis is based on NLP, we focus on processing a large volume of tweets rather than manually reading all of them, thus future studies may complement our approach by using qualitative methods to assess the specific arguments used by bots.

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Section: Discussionmentioning

confidence: 99%

(Re)shaping online narratives: when bots promote the message of President Trump during his first impeachment

Galgoczy

Phatak

Vinson

et al. 2022

PeerJ Computer Science

View full text Add to dashboard Cite

show abstract

“…The current information society to a period of rapid development, technology is very developed, the Internet technology has completely penetrated people's daily lives, changing people's way of life [1]. As an emerging thing, the advantages of the network have been played to the fullest, and the ensuing network culture has a great impact on the spiritual world of secondary school students [2]. Secondary school students are dealing with brand new challenges in their ideological and political education at the same time.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Teaching Reform of Middle School Ideological and Political Classroom Based on the Background of Internet

Deng,

Chen

2024

Applied Mathematics and Nonlinear Sciences

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The combination of Internet technology and education will continue to promote the change of the traditional education model, and will inevitably have a far-reaching impact on the reform of the education field. The wisdom classroom vector model is used to establish a secondary school classroom for ideological and political wisdom in this paper. In the smart classroom, students can recognize facial expressions by using GAN and tripartite consistency loss function. The ANM-CFM action recognition model is formed by the combination of the adaptive normalization module and covariance matrix fusion. For the effectiveness of the intelligent classroom of secondary school ideology and politics proposed in this paper with the related classroom behavior intelligent recognition method, the validation is carried out using example data. The results show that the first 200 frames in the smart classroom are dominated by the teacher’s lecture, and the students’ hand-raising interaction moments are mainly distributed between 200 and 400 frames. At the end of the teaching experiment, the classroom engagement level of the students in the experimental class was 9.037±0.532 points, the thinking level score of the experimental class exceeded 0.5 points compared with that of the control class, and the student’s satisfaction scores for the learning environment of the smart classroom were all over 2.4 points. The adoption of smart classrooms in the background of the Internet can realize the innovative reform of secondary school ideological and political classroom teaching and provide a new guarantee for improving the level of students’ thinking literacy.

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Mapping Intersections of Politics and Information in Twenty-First-Century Cyberculture

Cited by 2 publications

References 8 publications

(Re)shaping online narratives: when bots promote the message of President Trump during his first impeachment

(Re)shaping online narratives: when bots promote the message of President Trump during his first impeachment

Exploring the Teaching Reform of Middle School Ideological and Political Classroom Based on the Background of Internet

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