Strategies and Influence of Social Bots in a 2017 German state election - A case study on Twitter

Brachten, Florian; Stieglitz, Stefan; Hofeditz, Lennart; Kloppenborg, Katharina; Reimann, Annette

doi:10.48550/arxiv.1710.07562

Cited by 6 publications

(8 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The annotated evidence form positive examples, and we randomly sample 32 negative example sentences from the retrieved documents. We have two flavors of the fine-tuned model: EnmBERT only selects English negative sentences and EnRomBERT selects English (5) and Romanian (27) negative sentences. Claims are in English.…”

Section: Methodsmentioning

confidence: 99%

“…Online Disinformation. Previous disinformation studies focused on election related activity on social media platforms like Twitter, botnet generated hyperpartisan news, 2016 US presidential election [3][4][5]13]. To combat online disinformation via claim verification one must retrieve reliable evidence at scale since fake news tend to be more viral and spread faster [30], [27], [41], [35].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Multilingual Evidence Retrieval and Fact Verification to Combat Global Disinformation: The Power of Polyglotism

Roberts¹

2020

Preprint

View full text Add to dashboard Cite

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Multilingual Evidence Retrieval and Fact Verification to Combat Global Disinformation: The Power of Polyglotism

Roberts¹

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Trump promised to build a wall along the Mexican border to secure the country and mentioned this issue on Twitter often. Social bots were utilized to influence several important political debates and events previously (Bessi & Ferrara, 2016;Brachten et al, 2017;Stieglitz et al, 2017), and they were activated during the election campaign of Donald Trump (Schäfer et al, 2017), thus it can be expected that bots were also partaking in the border wall discussion. Therefore, it is essential to investigate whether social bots got involved in the building the wall discourse, and to what extent they participated and developed the discussion.…”

Section: Multiple Case Studiesmentioning

confidence: 99%

Bot Politics: The Affordances of Twitter and Nonhuman Participation

Momeni

2024

Preprint

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.

show abstract

“…There are several reports on the usage of bots in Twitter to manipulate that social network [35,36]. Just to mention some examples the bots has been used to interfere in elections in Brazil [2], Japan [63], USA [4,37], Germany [6] and the UK [35]. For example in the USA bots were used to influence the social media discussion on the presidential debates.…”

Section: Technological Attacksmentioning

confidence: 99%

Online Disinformation and the Role of Wikipedia

Saez-Trumper

2019

Preprint

View full text Add to dashboard Cite

The aim of this study is to find key areas of research that can be useful to fight against disinformation on Wikipedia. To address this problem we perform a literature review trying to answer three main questions: (i) What is disinformation? (ii)What are the most popular mechanisms to spread online disinformation? and (iii) Which are the mechanisms that are currently being used to fight against disinformation?. In all these three questions we take first a general approach, considering studies from different areas such as journalism and communications, sociology, philosophy, information and political sciences. And comparing those studies with the current situation on the Wikipedia ecosystem. We found that disinformation can be defined as non-accidentally misleading information that is likely to create false beliefs. While the exact definition of misinformation varies across different authors, they tend to agree that disinformation is different from other types of misinformation, because it requires the intention of deceiving the receiver. A more actionable way to scope disinformation is to define it as a problem of information quality. In Wikipedia quality of information is mainly controlled by the policies of neutral point of view and verifiability. The mechanisms used to spread online disinformation include the coordinated action of online brigades, the usage of bots, and other techniques to create fake content. Underresouced topics and communities are especially vulnerable to such attacks. The usage of sock-puppets is one of the most important problems for Wikipedia. The techniques used to fight against information on the internet, include manual fact checking done by agencies and communities, as well as automatic techniques to assess the quality and credibility of a given information. Machine learning approaches can be fully automatic or can be used as tools by human fact checkers. Wikipedia and especially Wikidata play double role here, because they are used by automatic methods as ground-truth to determine the credibility of an information, and at the same time (and for that reason) they are the target of

show abstract

Strategies and Influence of Social Bots in a 2017 German state election - A case study on Twitter

Cited by 6 publications

References 0 publications

Multilingual Evidence Retrieval and Fact Verification to Combat Global Disinformation: The Power of Polyglotism

Multilingual Evidence Retrieval and Fact Verification to Combat Global Disinformation: The Power of Polyglotism

Bot Politics: The Affordances of Twitter and Nonhuman Participation

Online Disinformation and the Role of Wikipedia

Contact Info

Product

Resources

About