Titlebook: Disinformation in Open Online Media; Second Multidiscipli Max van Duijn,Mike Preuss,Suzan Verberne Conference proceedings 2020 Springer Nat

不妥協(xié)

Abutment

,#ArsonEmergency and Australia’s “Black Summer”: Polarisation and Misinformation on Social Media,burning spread quickly on Twitter, particularly using the hashtag .. Misinformation and bot- and troll-like behaviour were detected and reported by social media researchers and the news soon reached mainstream media. This paper examines the communication and behaviour of two polarised online communi

Aesthete

How Identity and Uncertainty Affect Online Social Influence,and population-wide systems. In this study, three agent-based simulations (ABSs) were developed to model opinion dynamics in an online social media context. The main focus was to test the effects of ‘social identity’ and ‘certainty’ on social influence. When humans interact, they influence each othe

FACET

Do Online Trolling Strategies Differ in Political and Interest Forums: Early Results,obal warming, and interest-based forums that deal with people’s personal interests. Based on previous research, we consider trolling as context-bound and suggest that relevance theory and common grounding theory can explain why people may attend and react to certain types of troll posts in one forum

大漩渦

On the Robustness of Rating Aggregators Against Injection Attacks,odology, we propose to contain the consequences of an attack launched by a fake reviewer who attaches arbitrary scores to the review target. We demonstrate that, by simply changing the score aggregator, the review site can withstands smart and targeted attacks, even carried out for an extended perio

Classify

FakeYou! - A Gamified Approach for Building and Evaluating Resilience Against Fake News,nformation reaches a new level with the rise of the internet and participatory platforms. Due to Facebook and Co., purposeful false information - often called fake news - can be easily spread by everyone. Because of high data volatility and variety in content types (text, images,...) debunking of fa

Euthyroid

indigenous

Near Real-Time Detection of Misinformation on Online Social Networks, articles and classify these articles as misinformation or trusted information. We do this by extracting a comprehensive set of network and linguistic features and propose a deep learning model that combines both feature types. Experiments on real data demonstrate that our proposed method detects mi

Minatory

Multi-modal Analysis of Misleading Political News,to abuse these platforms through the dissemination of misinformation. As people are generally awash in information, they can sometimes have difficulty discerning misinformation propagated on these web platforms from truthful information. They may also lean too heavily on information providers or soc

allergy