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DSAA 2020 : Special Session FAKE NEWS, BOTS AND TROLLS

Sydney, Australia
Event Date: Oct 04, 2020 - Oct 09, 2020
Submission Deadline: May 24, 2020
Notification of Acceptance: Jul 26, 2020

Categories

 
NLP

About

Fake news has become one of the main threats to our society. Although fake news is not a new phenomenon, the exponential growth of social media has offered an easy platform for its fast and wide propagation. The threat is even greater when fake news dissemination has a political or an ideological purpose, as it happens during electoral campaigns or during extreme events able to endanger political regimes, such as epidemics. Bots are commonly related to fake news spreading. They can artificially inflate the popularity of an opinion or a political candidate, as well as undermine the reputation of a targeted politician and hinder an opposing view, by repeatedly spamming contents produced by disinformation outlets. Other actors of misbehaviour in social media are trolls that offend people, dominate online discussions, and in general try to manipulate people's opinion by triggering hate and anger, with the aim of interfering with the regular public debate.

In this special session we would like the research community to share how the above problems need to be addressed from several interdisciplinary perspectives. Special emphasis will be on how news broadcasting corporations fact check claims by politicians, public figures, advocacy groups and institutions engaged in the public debate; how crowd signals in social media can be used to flag fake news; how online user activity fingerprints can be leveraged in order to detect a malicious use of social networks; how pieces of disinformation spread on social networks; how fake news broadcasters cooperate to conduct misinformation campaigns; how to design a semi-automated system that could trace and/or verify news shared online, helping journalists to identify disinformation.

Call For Paper

Areas of interest include, but are not limited to:

Computational approaches to the following tasks:

  • Detection of fake news spreaders

  • Detection of bots and trolls

  • Identification of information generated by bots and trolls

  • Patterns in fake news propagation

  • Credibility assessment of online information and information sources

  • Detection of polarization in online communities

  • Multimodal fake news detection

  • Eary detection of fake news

  • Fake news prevention, filtering and containment

  • Analysis/detection of multi-platform fake news spreading

Others:

  • Measurements and analysis of fake news impact

  • Resources for journalists for fake news detection

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