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Identifying Top-k Consistent News-Casters on Twitter

Published: 17 October 2015 Publication History

Abstract

News-casters are Twitter users who periodically pick up interesting news from online news media and spread it to their followers' network. Existing works on Twitter user analysis have only analysed a pre-defined set of users for user modeling, influence analysis and news recommendation. The problem of identifying prominent, trustworthy and consistent news-casters is unaddressed so far. In this paper, we present a framework, NCFinder, to discover top-k consistent news-casters directly from Twitter. NCFinder uses news headlines published in online news sources to periodically collect authentic news-tweets and processes them to discover news-casters, news sources and news concepts. Next, NCFinder builds a tripartite graph among news-casters, news source and news concepts and employs HITS algorithm on it to score the news-casters on daily basis. The daily score profiles of the news-casters collected over a time-period are then used to infer top-$k$ consistent news-casters. We run NCFinder from 11th Nov. to 24th Nov., 2014 and discover top-100 consistent news-casters and their profile information.

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  • (2017)Mining Credible and Relevant News from Social NetworksBig Data Analytics10.1007/978-3-319-72413-3_6(90-102)Online publication date: 25-Nov-2017

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cover image ACM Conferences
CIKM '15: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management
October 2015
1998 pages
ISBN:9781450337946
DOI:10.1145/2806416
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2015

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Author Tags

  1. news
  2. news-tweet
  3. tweet authentication
  4. twitter
  5. user profiling

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CIKM'15
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CIKM '15 Paper Acceptance Rate 165 of 646 submissions, 26%;
Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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  • (2017)Mining Credible and Relevant News from Social NetworksBig Data Analytics10.1007/978-3-319-72413-3_6(90-102)Online publication date: 25-Nov-2017

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