Insight4News: Connecting News to Relevant Social Conversations

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Title: Insight4News: Connecting News to Relevant Social Conversations
Authors: Shi, Bichen
Ifrim, Georgiana
Hurley, Neil J.
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Date: 19-Sep-2014
Online since: 2017-05-19T11:44:33Z
Abstract: We present the Insight4News system that connects news articles to social conversations, as echoed in microblogs such as Twitter. Insight4News tracks feeds from mainstream media, e.g., BBC, Irish Times, and extracts relevant topics that summarize the tweet activity around each article, recommends relevant hashtags, and presents complementary views and statistics on the tweet activity, related news articles, and timeline of the story with regard to Twitter reaction. The user can track their own news article or a topic-focused Twitter stream. While many systems tap on the social knowledge of Twitter to help users stay on top of the information wave, none is available for connecting news to relevant Twitter content on a large scale, in real time, with high precision and recall. Insight4News builds on our award winning Twitter topic detection approach and several machine learning components, to deliver news in a social context.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: Springer
Start page: 473
End page: 476
Series/Report no.: Lecture Notes in Computer Science
Copyright (published version): 2014 Springer
Keywords: Media analyticsNews trackingSocial mediaTwitterSummarization
DOI: 10.1007/978-3-662-44845-8_38
Language: en
Status of Item: Peer reviewed
Is part of: Calders, T., Esposito, F., Hullermeier, E. and Meo, R. (eds.). Proceedings Part III: ECML/PKDD 2014: European Conference on Machine Learning and Knowledge Discovery in Databases (Volume 8726)
Conference Details: ECML/PKDD 2014: European Conference on Machine Learning and Knowledge Discovery in Databases, Nancy, France, 15-19 September 2014
ISBN: 9783662448458
Appears in Collections:Insight Research Collection

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