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Time-based Microblog Distillation

Abstract

This paper presents a simple approach for identifying relevant and reliable news from the Twitter stream, as soon as they emerge. The approach is based on a near-real time systems for sentiment analysis on Twitter, implemented by Fondazione Ugo Bordoni, and properly modified in order to detect the most representative tweets in a specified time slot. This work represents a first step towards the implementation of a prototype supporting journalists in discovering and finding news on Twitter

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