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Be In The Know: Connecting News Articles to Relevant Twitter Conversations

Publication Type: 
Refereed Conference Meeting Proceeding
In this paper we propose a framework for tracking and automatically connecting news articles to Twitter conversations as captured by Twitter hashtags. For example, such a system could alert journalists about news that get a lot of Twitter reaction, so they can investigate those conversations for new developments in the story, promote their article to a set of interested consumers, or discover general sentiment towards the story. Mapping articles to hashtags is nevertheless challenging, due to different language style of articles versus tweets, the streaming aspect, and user behavior when marking tweet-terms as hashtags. We track the IrishTimes RSS-feed and a focused Twitter stream over a two months period, and present a system that assigns hashtags to each article, based on its Twitter echo. We propose a machine learning approach for classifying articlehashtag pairs. Our empirical study shows that our system delivers high precision for this task.
Conference Name: 
ECML/PKDD PhD Paper Track
ECML/PKDD PhD Paper Track
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Conference Location: 
National University of Ireland, Dublin (UCD)
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