research-article

SNS-based issue detection and related news summarization scheme

Authors:

Eenjun HwangAuthors Info & Claims

ICUIMC '14: Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication

Article No.: 114, Pages 1 - 7

https://doi.org/10.1145/2557977.2558089

Published: 09 January 2014 Publication History

Abstract

Due to the unprecedented popularity of social network services (SNSs), such as Twitter and Facebook, means that a huge number of user documents are created and shared constantly via SNSs. Given the volume of user documents, browsing documents in a selective manner based on personal interests is a time-consuming and laborious task. Therefore, in the case of Twitter, trend keyword lists are provided for the user's convenience. However, it is still not easy to determine the details based on a few simple keywords. The keywords usually relate to the hot issues at any time so many documents will contain pertinent details, such as news on the Internet. Thus, to provide detailed information about an issue, it is necessary to identify relationships among them. In this study, we developed a SNS-based issue detection and related news summarization scheme. To evaluate the effectiveness of our scheme, we implemented a prototype system and performed various experiments. We present some of the results.

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Cited By

Iglesias JTiemblo ALedezma ASanchis A(2016)Web news mining in an evolving frameworkInformation Fusion10.1016/j.inffus.2015.07.00428:C(90-98)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1016/j.inffus.2015.07.004
Purwitasari DFatichah CArieshanti IHayatin N(2015)K-medoids algorithm on Indonesian Twitter feeds for clustering trending issue as important terms in news summarization2015 International Conference on Information & Communication Technology and Systems (ICTS)10.1109/ICTS.2015.7379878(95-98)Online publication date: Sep-2015
https://doi.org/10.1109/ICTS.2015.7379878

Index Terms

SNS-based issue detection and related news summarization scheme
1. Information systems
  1. Information retrieval
2. Theory of computation
  1. Semantics and reasoning
    1. Program reasoning
      1. Abstraction

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cover image ACM Conferences

ICUIMC '14: Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication

January 2014

757 pages

ISBN:9781450326445

DOI:10.1145/2557977

Conference Chairs:
Dongsoo S. Kim
Indiana University
,
Sang-Wook Kim
Hanyang University, Korea
,
General Chairs:
Suk-Han Lee
Sungkyunkwan University
,
Korea Lajos Hanzo
University of Southampton, UK
,
Roslan Ismail
Universiti Kuala Lumpur, Malaysia

Copyright © 2014 ACM.

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SIGAPP: ACM Special Interest Group on Applied Computing
SKKU: SUNGKYUNKWAN UNIVERSITY

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New York, NY, United States

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Published: 09 January 2014

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ICUIMC '14: The 8th International Conference on Ubiquitous Information Management and Communication

January 9 - 11, 2014

Siem Reap, Cambodia

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ICUIMC '14 Paper Acceptance Rate 116 of 407 submissions, 29%;

Overall Acceptance Rate 251 of 941 submissions, 27%

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Cited By

Iglesias JTiemblo ALedezma ASanchis A(2016)Web news mining in an evolving frameworkInformation Fusion10.1016/j.inffus.2015.07.00428:C(90-98)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1016/j.inffus.2015.07.004
Purwitasari DFatichah CArieshanti IHayatin N(2015)K-medoids algorithm on Indonesian Twitter feeds for clustering trending issue as important terms in news summarization2015 International Conference on Information & Communication Technology and Systems (ICTS)10.1109/ICTS.2015.7379878(95-98)Online publication date: Sep-2015
https://doi.org/10.1109/ICTS.2015.7379878

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