Hot Events Detection for Chinese Microblogs Based on the TH-LDA Model
Jiahui Chen, Qingxia Shang, Hailing Xiong
Available Online December 2018.
- https://doi.org/10.2991/tlicsc-18.2018.26How to use a DOI?
- Hot Events Detection; LDA Model; Chinese Microblogs.
- Nowadays, many unexpected topics in the society initiate on the microblog platform and spread rapidly, and some of them finally become hot events. The technology for detecting these hot events on the microblog platform, has exerted a very positive influence on the discovery of the latest social hotspots and the timely perception of the internet public opinion. This paper analyzed the studies for detecting microblog hot events, and disclosed the existing methods may omit the untagged microblogs and thus lead to the failure to detect the subevents. To address this issue, we combined Hashtag and Time with the topic model of LDA, and proposed the TH-LDA model to improve the effectiveness of hot events detection for Chinese microblogs. Experiments on microblogs datasets demonstrate that the proposed TH-LDA model can effectively obtain untagged microblogs, and then realize the subevents detection of hot events with a high accuracy.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jiahui Chen AU - Qingxia Shang AU - Hailing Xiong PY - 2018/12 DA - 2018/12 TI - Hot Events Detection for Chinese Microblogs Based on the TH-LDA Model BT - 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/tlicsc-18.2018.26 DO - https://doi.org/10.2991/tlicsc-18.2018.26 ID - Chen2018/12 ER -