Ushio: Analyzing News Media and Public Trends in Twitter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this information age, Social Networking Services contribute a significant amount of contents in creating a knowledge based society. Nowadays, there are more than 500 million tweets sent per day in Twitter. Such drastic growth of contents brings new opportunities for human beings to discover their surroundings more effectively in a timely manner. Moreover, these types of services evolve not only in a perspective of scalability, but also in the view of indicating more meaningful information regarding what happens in the world. Numerous news agencies are broadcasting breaking news via Twitter and people would like to leave comments with their own opinions as well. However, there are differences between events that news media are more willing to cover and news stories that people are more interested in. Furthermore, as people are becoming the largest sensor network, trending topics are not only led by media, but also by the public, and hence it is worth pondering how they affect each other. In this paper, we focus on studying these concerns by building a system, Ushio, analyzing Twitter streams in both the tweets updated by multiple news agencies and those appearing in the public timeline. We describe our design and implementation of this system, which extracts named entities from the Twitter streams and generates corresponding statistics with its relational model. We then show how we use these data to find trending topics and real focus from both media and the public, as well as discover their related topics along with the correlation indicating the leading role between them for assorted topics.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015
EditorsOmer Rana, Rajkumar Buyya, Ioan Raicu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages424-429
Number of pages6
ISBN (Electronic)9780769556970
DOIs
StatePublished - 2015
Event8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015 - Limassol, Cyprus
Duration: Dec 7 2015Dec 10 2015

Publication series

NameProceedings - 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, UCC 2015

Other

Other8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015
Country/TerritoryCyprus
CityLimassol
Period12/7/1512/10/15

Keywords

  • Named Entity
  • Relational Data
  • Social Networking
  • Twitter

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications

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