Ranking Tweets Considering Trust and Relevance
Srijith Ravikumar, Raju Balakrishnan, Subbarao Kambhampati

TL;DR
This paper introduces a method for ranking tweets by integrating trustworthiness and relevance, using a three-layer graph model to improve precision and trustworthiness in microblog content.
Contribution
It presents a novel multi-layer graph approach to assess trust and popularity in tweets, considering relationships between users, tweets, and web pages.
Findings
Improved precision over baseline methods
Enhanced trustworthiness scores
Acceptable computation timings
Abstract
The increasing popularity of Twitter and other microblogs makes improved trustworthiness and relevance assessment of microblogs evermore important. We propose a method of ranking of tweets considering trustworthiness and content based popularity. The analysis of trustworthiness and popularity exploits the implicit relationships between the tweets. We model microblog ecosystem as a three-layer graph consisting of : (i) users (ii) tweets and (iii) web pages. We propose to derive trust and popularity scores of entities in these three layers, and propagate the scores to tweets considering the inter-layer relations. Our preliminary evaluations show improvement in precision and trustworthiness over the baseline methods and acceptable computation timings.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMisinformation and Its Impacts · Spam and Phishing Detection · Access Control and Trust
