Credibility in social media: opinions, news, and health information—a survey

Abstract

In the Social Web scenario, where large amounts of User Generated Content diffuse through Social Media, the risk of running into misinformation is not negligible. For this reason, assessing and mining the credibility of both sources of information and information itself constitute nowadays a fundamental issue. Credibility, also referred as believability, is a quality perceived by individuals, who are not always able to discern with their cognitive capacities genuine information from the fake one. For this reason, in the recent years several approaches have been proposed to automatically assess credibility in Social Media. Most of them are based on data‐driven models, i.e., they employ machine‐learning techniques to identify misinformation, but recently also model‐driven approaches are emerging, as well as graph‐based approaches focusing on credibility propagation. Since multiple social applications have been developed for different aims and in different contexts, several solutions have been considered to address the issue of credibility assessment in Social Media. Three of the main tasks facing this issue and considered in this article concern: (1) the detection of opinion spam in review sites, (2) the detection of fake news and spam in microblogging, and (3) the credibility assessment of online health information. Despite the high number of interesting solutions proposed in the literature to tackle the above three tasks, some issues remain unsolved; they mainly concern both the absence of predefined benchmarks and gold standard datasets, and the difficulty of collecting and mining large amount of data, which has not yet received the attention it deserves. WIREs Data Mining Knowl Discov 2017, 7:e1209. doi: 10.1002/widm.1209 This article is categorized under: Algorithmic Development > Web Mining Application Areas > Science and Technology Technologies > Machine Learning

Crowdsourcing Truthfulness: The Impact of Judgment Scale and Assessor Bias

“…The credibility of information available online may vary and the presence of untrustworthy information has big implications on our safety online [5,12,15]. The recent increase of misinformation online is to be blamed on technologies that have enabled the next level of strategic politic propaganda.…”

A New Application of Social Impact in Social Media for Overcoming Fake News in Health

“…The previous studies reviewed have been useful in clarifying how health information is spread in social media, identifying the positive and negative impacts [6,7]. Regarding the adverse effects of using social media to spread misinformation, there is evidence of the harmful consequences to global health and well-being, becoming one of the most significant challenges for public health systems today [5,9].…”

“…From diverse fields of knowledge linked to health issues, it can be stated that social media can have both a positive and a negative impact on public health [6,7]. On the one hand, the combination of artificial intelligence and big data can help public health providers identify pandemic diseases in real time, improving the coordination of the response of public health systems through information sharing and improving surveillance and diagnostics.…”

“…Most of them are based on data-based models, i.e., they use automatic learning techniques to identify misinformation. Based on these techniques, different applications have been developed with different objectives and in different contexts, such as detecting opinion spam on review sites, detecting false news and spam in microblogging, and assessing the credibility of online health information [6,42,43]. These techniques include both human intervention and algorithms to verify the veracity of information across technologies, such as artificial intelligence (AI) and natural language processing (NLP) [44].…”

Credibility Dimensions for Islamic Information in Social Media

“…Among the dimensions that make information credible include medium, content, source, technology, and social [1], [2]. In this age of outpouring of information on the Internet, users are becoming more demanding of credible and reliable information sources [3], [4]. Previous works recommend different approaches for measuring offline and online information credibility [5] [6].…”