Ranking Tweets Considering Trust and Relevance

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.