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ItemCan Machines Learn to Detect Fake News? A Survey Focused on Social Media( 2019-01-08)Through a systematic literature review method, in this work we searched classical electronic libraries in order to find the most recent papers related to fake news detection on social medias. Our target is mapping the state of art of fake news detection, defining fake news and finding the most useful machine learning technique for doing so. We concluded that the most used method for automatic fake news detection is not just one classical machine learning technique, but instead a amalgamation of classic techniques coordinated by a neural network. We also identified a need for a domain ontology that would unify the different terminology and definitions of the fake news domain. This lack of consensual information may mislead opinions and conclusions.
ItemCollective Action in Digital Age: A Multilevel Approach( 2019-01-08)This theory paper proposes a multilevel model for analyzing collective actions for social change in the networked information age. The model includes four levels of agency (individual, group, organizational, and bot) and three levels of affordance (application, network infrastructure, and socio-political system) to help analyze social change dynamics which have become more decentralized. Mechanisms and outcomes of interactions between factors in the model should be considered to offer a more complete picture of social change facilitated by digital communication technologies. Empirical studies based on this model will help illuminate the evolution of communication structures as well as the affordances that evolution provides for social change. Moreover, speedy disintermediation in networked spaces and interactions between the levels in this process provides an opportunity for better understanding information generation and mediation in this rapidly changing media environment.
ItemOnline Disinformation and the Psychological Bases of Prejudice and Political Conservatism( 2019-01-08)It is widely believed that the impact of fake news, internet rumors, hoaxes, deceptive memes etc. are spilling into the physical world from the virtual world. In fact, social media has had a significant role in the origination and spread of such deceptive communication, as social media users often lack awareness of the intentional manipulation of online content and are easily tricked into believing unverifiable content. In an increasingly polarized world where social media and the internet have pushed people to live inside “echo chambers” and “filter bubbles,” people consciously and unconsciously are exposed only to content that reinforce their confirmation bias. In such a scenario, people only agree with content that aligns with their preexisting beliefs and disagree with or label as “fake” content that is opposed to their worldview. This paper proposes to study the psychological differences that cause people to either agree or disagree with such prejudiced and ideologically oriented online disinformation.