TweetCred: Real-Time Credibility Assessment of Content on Twitter

Abstract

During sudden onset crisis events, the presence of spam, rumors and fake content on Twitter reduces the value of information contained on its messages (or "tweets"). A possible solution to this problem is to use machine learning to automatically evaluate the credibility of a tweet, i.e. whether a person would deem the tweet believable or trustworthy. This has been often framed and studied as a supervised classification problem in an off-line (post-hoc) setting. In this paper, we present a semi-supervised ranking model for scoring tweets according to their credibility. This model is used in TweetCred , a real-time system that assigns a credibility score to tweets in a user's timeline. TweetCred , available as a browser plug-in, was installed and used by 1,127 Twitter users within a span of three months. During this period, the credibility score for about 5.4 million tweets was computed, allowing us to evaluate TweetCred in terms of response time, effectiveness and usability. To the best of our knowledge, this is the first research work to develop a real-time system for credibility on Twitter, and to evaluate it on a user base of this size.

Crisis analytics: big data-driven crisis response

“…The Verily project (Verily) crowdsources the task of verification by seeking rapid crowdsource evidence (in terms of an affirmative or negative answer) to answer verification questions. The TweetCred is a web-and ML-based plug-in that can be used to automatically detect non-credible tweets and fake images being shared on Twitter in real time (Gupta et al 2014).…”

Quality management architecture for social media data

“…Classifiers trained based on a similar approach have been developed for detecting newsworthiness and credibility of tweets [7]. TweetCred is a real time system for assigning a credibility score to a Twitter user's time line [36]. The usefulness of comments in Flickr and YouTube has been studied [8].…”

“…While several methods and algorithms can be utilised for social media data analysis [23], typically supervised learning based methods have been used for evaluating quality aspects of social media data [6,36,38]. In order to understand quality aspects of social media data, different approaches have been proposed for management of quality in social media data [9-11, 17, 18].…”

Classifying Short Text in Social Media: Twitter as Case Study

“…This motivated Gupta et al at Qatar Computing Research Institute (QCRI) and the Indraprastha Institute of Information Technology (IIIT) to develop an evaluation tool. The tool, called "tweetcred," [25] is publicly available for download from the Google Chrome Extensions store 5 . The tool is integrated with the Twitter website to show a meter, beside a username, with a scale of seven stars that shows an evaluation of the user's credibility.…”