Detecting Hot Topics in Sina Weibo Based on Opinion Leaders
Donghui Li, Yuqing Zhang, Xin Chen, Long Cao, Chuanfeng Zhou
Available Online January 2014.
- https://doi.org/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.
- 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 -