State Propaganda on Twitter

Kießling, Bastian; Homburg, Jan; Drozdzynski, Tanja; Burkhardt, Steffen

doi:10.1007/978-3-030-39627-5_14

Cited by 3 publications

(4 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This mixture may reflect that the use of bots in the political sphere is partly a state-sponsored activity. That is, various states intervene and their different preferences produce a heterogeneous set of tweets ( Kießling et al, 2019 ; Stukal et al, 2019 ). Although studies on centrally coordinated disinformation campaigns often focus on how one specific entity (attempts to) shape the public opinion ( Keller et al, 2020 ; Im et al, 2020 ), complex events involve multiple entities promoting different messages.…”

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

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.

show abstract

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

“…These operations are often complex in nature and make use of cultivated networks of nodes known to be efficient at communicating a narrative to the largest possible audience in the shortest amount of time (Guarino et al, 2020). They may also be carried out by anyone with internet access, from individuals like Farah Baker (Wolf, 2015) to terrorist groups (Weimann, 2010) and state governments (Kießling et al, 2020). Understanding the success of these operations requires an explanation of the networks that make them possible and how they are employed.…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

“…Beyond Russia, Iran has been observed using Twitter bots and propaganda accounts to attempt to influence the foreign and public policies involving Saudi Arabia, with the state actively promoting biased hashtags and retweeting identifiable propaganda sources (Kießling et al, 2020). Kießling et al (2020) note that Iran's Twitter campaign activity tends to spike coinciding with major political events, although they also find that the majority of Iran's attempts at influencing foreign policy were unsuccessful. China has also been observed employing Twitter propaganda strategies, notably surrounding public discourse concerning territorial disputes in the South China Sea, in which most of the 19 "important China actors in the #SouthChinaSea conversation" were identified as representing "central-level state news media" (Nip & Sun, 2022, p. 61).…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Twitter Propaganda Operations: Analyzing Sociopolitical Issues in Saudi Arabia

Albert,

Aleroud,

Yang

et al. 2023

Social Media + Society

View full text Add to dashboard Cite

The purpose of this article is to explore Arabic-language Tweets based out of Saudi Arabia to investigate the social media landscape. Specifically, this article seeks to address the question, “What thematic issues concerning the U.S. socio-political landscape are present in Arabic-language Twitter postings?” And, “To what extent can these issues be described as propagandic in nature?” To do so, we propose a machine-learning and artificial intelligence span detection approach to identify propaganda Tweets in Middle Eastern Countries, with a focus on Saudi Arabia. As opposed to previous work, this article maps and investigates different propaganda categories using the BEND Social Cyber Security framework. This article then proceeds to a case study analysis of state-sponsored targeted propaganda from Saudi Arabia and briefly describes the categories of propaganda uncovered. We then relate those categories to the BEND Framework and conclude with policy recommendations and discussion.

show abstract