Identification of Credibility Content Measures for Twitter and Sina-Weibo Social Networks

摘要

Twitter has been the most pivotal platform for sharing information, news and messages among the connected people. In the era of social media where a huge amount of information is being shared over the internet, the task of determining the authenticity, integrity, and nature of the information received has become significant for the users. So far, a number of rigorous efforts have been made on social networks such as Twitter and Sina Weibo to identify the specific features for assisting other users in determining the credibility of the available content. These features have been categorized into three categories, namely, content-based features, user-based features and hybrid features. This paper is an attempt to rigorously survey the approaches employed for the detection of rumors on social networks. Furthermore, we have highlighted various corpus, data collection methods, features responsible for finding and estimating credibility along with different machine learning techniques in order to assist the users working in this domain.