منابع مشابه
Automatic Detection of Fake News
The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online...
متن کاملExploiting Tri-Relationship for Fake News Detection
Social media for news consumption is becoming popular nowadays. The low cost, easy access and rapid information dissemination of social media bring benefits for people to seek out news timely. However, it also causes the widespread of fake news, i.e., low-quality news pieces that are intentionally fabricated. The fake news brings about several negative effects on individual consumers, news ecos...
متن کاملStance Detection for Fake News Identification
The latest election cycle generated sobering examples of the threat that fake news poses to democracy. Primarily disseminated by hyper-partisan media outlets, fake news proved capable of becoming viral sensations that can dominate social media and influence elections. To address this problem, we begin with stance detection, which is a first step towards identifying fake news. The goal of this p...
متن کاملPolarization and Fake News: Early Warning of Potential Misinformation Targets
Users polarization and confirmation bias play a key role in misinformation spreading on online social media. Our aim is to use this information to determine in advance potential targets for hoaxes and fake news. In this paper, we introduce a general framework for promptly identifying polarizing content on social media and, thus, “predicting” future fake news topics. We validate the performances...
متن کاملFake News Detection Through Multi-Perspective Speaker Profiles
Automatic fake news detection is an important, yet very challenging topic. Traditional methods using lexical features have only very limited success. This paper proposes a novel method to incorporate speaker profiles into an attention based LSTM model for fake news detection. Speaker profiles contribute to the model in two ways. One is to include them in the attention model. The other includes ...
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ژورنال
عنوان ژورنال: Digital Threats: Research and Practice
سال: 2020
ISSN: 2692-1626,2576-5337
DOI: 10.1145/3377478