Proceedings of the 2016 International Seminar on Education Innovation and Economic Management (SEIEM 2016)

Evolution Analysis of Topics on Social Media Based on the Co-word Network

Authors
Zhuoqun Chen, Xu Sun
Corresponding Author
Zhuoqun Chen
Available Online December 2016.
DOI
https://doi.org/10.2991/seiem-16.2016.130How to use a DOI?
Keywords
Co-word Network, Community, Social Media, Topic Identification, Topic Evolution
Abstract
For the information in the social media, methods of topic feature selection in different time have been put forward to build the dynamic co-word network. The community discovery algorithm is applied to divide the co-word network on the basis of communities. And the co-word network community stands for the subtopics of the topics in the social media. On the basis of the comparability identification of subtopics in different time, the evolution process of subtopics is divided into three stages as the subtopic production, the subtopic diffusion and the subtopic fading. The empirical analysis shows that representing subtopics by using the co-word network community has such advantages as the intelligibility and the noise reduction; the development path and variation trend of subtopics can be clearly clarified on the basis of the co-word network community.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Seminar on Education Innovation and Economic Management (SEIEM 2016)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
December 2016
ISBN
978-94-6252-273-2
ISSN
2352-5398
DOI
https://doi.org/10.2991/seiem-16.2016.130How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Zhuoqun Chen
AU  - Xu Sun
PY  - 2016/12
DA  - 2016/12
TI  - Evolution Analysis of Topics on Social Media Based on the Co-word Network
BT  - 2016 International Seminar on Education Innovation and Economic Management (SEIEM 2016)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/seiem-16.2016.130
DO  - https://doi.org/10.2991/seiem-16.2016.130
ID  - Chen2016/12
ER  -