Proceedings of the 2014 International Conference on Computer, Communications and Information Technology

Detecting Hot Topics in Sina Weibo Based on Opinion Leaders

Authors
Donghui Li, Yuqing Zhang, Xin Chen, Long Cao, Chuanfeng Zhou
Corresponding Author
Donghui Li
Available Online January 2014.
DOI
https://doi.org/10.2991/ccit-14.2014.47How to use a DOI?
Keywords
Sina Weibo, hot topic, discriminant model, opinion leader, word co-occurrence graph
Abstract
Sina Weibo, as one of the most popular and fast growing social network, has gradually become the field where hot topics appear, propagate, and outbreak. In order to discriminate and find out hot topics in micro-blog information, we conduct a series of studies on Sina Weibo, and one of our key findings is that opinion leaders play a very important role in the propagation of hot topics. A smart discriminant model is proposed in this paper to detect hot topics in time, which takes the structure information and propagation characteristics of Sina Weibo as well as the users’ influence into consideration. Moreover, word co-occurrence graph is used to extract and display topics. This model has some excellent characters such as a low coupling degree between modules and a low requirement for the amount of data. By experimental verification, it can detect hot topics effectively.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2014 International Conference on Computer, Communications and Information Technology (CCIT 2014)
Part of series
Advances in Intelligent Systems Research
Publication Date
January 2014
ISBN
978-90786-77-97-0
ISSN
1951-6851
DOI
https://doi.org/10.2991/ccit-14.2014.47How 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  - Donghui Li
AU  - Yuqing Zhang
AU  - Xin Chen
AU  - Long Cao
AU  - Chuanfeng Zhou
PY  - 2014/01
DA  - 2014/01
TI  - Detecting Hot Topics in Sina Weibo Based on Opinion Leaders
BT  - 2014 International Conference on Computer, Communications and Information Technology (CCIT 2014)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccit-14.2014.47
DO  - https://doi.org/10.2991/ccit-14.2014.47
ID  - Li2014/01
ER  -