Detecting Hot Topics in Sina Weibo Based on Opinion Leaders
- 10.2991/ccit-14.2014.47How to use a DOI?
- Sina Weibo, hot topic, discriminant model, opinion leader, word co-occurrence graph
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.
- © 2014, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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 - Proceedings of the 2014 International Conference on Computer, Communications and Information Technology PB - Atlantis Press SP - 178 EP - 181 SN - 1951-6851 UR - https://doi.org/10.2991/ccit-14.2014.47 DO - 10.2991/ccit-14.2014.47 ID - Li2014/01 ER -