Weaponising Social Media for Information Divide and Warfare

@article{Haq2022WeaponisingSM,
  title={Weaponising Social Media for Information Divide and Warfare},
  author={Ehsan-ul Haq and Gareth Tyson and Tristan Braud and Pan Hui},
  journal={Proceedings of the 33rd ACM Conference on Hypertext and Social Media},
  year={2022}
}
  • E. HaqGareth Tyson Pan Hui
  • Published 28 June 2022
  • Sociology
  • Proceedings of the 33rd ACM Conference on Hypertext and Social Media
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References

SHOWING 1-10 OF 10 REFERENCES

Twitter under crisis: can we trust what we RT?

The behavior of Twitter users under an emergency situation is explored and it is shown that it is posible to detect rumors by using aggregate analysis on tweets, and that the propagation of tweets that correspond to rumors differs from tweets that spread news.

Algorithmic amplification of politics on Twitter

This study carries out the most comprehensive audit of an algorithmic recommender system and its effects on political content, revealing that the political right enjoys higher amplification compared to the political left and that algorithmic amplification favors right-leaning news sources.

Identifying and characterizing user communities on Twitter during crisis events

A preliminary study to identify and characterize communities from a set of users who post messages on Twitter during crisis events, and shows that the top users represent the topics and opinions of all the users in the community with 81% accuracy on an average.

Profiling Fake News Spreaders on Social Media through Psychological and Motivational Factors

This work studies the characteristics and motivational factors of fake news spreaders on social media with input from psychological theories and behavioral studies and investigates whether the characteristics observed can be applied to the detection of fakeNews spreaders in a real social media environment.

Others Are to Blame: Whom People Consider Responsible for Online Misinformation

Determining who is responsible for online misinformation is an important problem. This research offers a multifaceted view of the public's perception of who is responsible for online misinformation.

Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media

This paper proposes a framework to quantify these distinct biases and applies this framework to politics-related queries on Twitter and found that both the input data and the ranking system contribute significantly to produce varying amounts of bias in the search results.

The 'Fairness Doctrine' lives on?: Theorizing about the Algorithmic News Curation of Google's Top Stories

This paper surveys US voters to elicit their familiarity and trust with these 56 news outlets and finds that some of the most frequent outlets are not familiar to all voters, or particularly trusted by voters of any political stripes.

Beyond Social Graphs: User Interactions in Online Social Networks and their Implications

This article proposes the use of “interaction graphs” to impart meaning to online social links by quantifying user interactions, and analyzes interaction graphs derived from Facebook user traces to validate several well-known social-based applications that rely on graph properties to infuse new functionality into Internet applications.

Social media platforms on the defensive as Russian-based disinformation about Ukraine spreads

  • 2022

Providing relevant notifications based on common interests between friends in a social networking system

  • US Patent
  • 2013