Abstract
Social media has become an important platform for people to express opinions, share information and communicate with others. Detecting and tracking topics from social media can help people grasp essential information and facilitate many security-related applications. As social media texts are usually short, traditional topic evolution models built based on LDA or HDP often suffer from the data sparsity problem. Recently proposed topic evolution models are more suitable for short texts, but they need to manually specify topic number which is fixed during different time period. To address these issues, in this paper, we propose a nonparametric topic evolution model for social media short texts. We first propose the recurrent semantic dependent Chinese restaurant process (rsdCRP), which is a nonparametric process incorporating word embeddings to capture semantic similarity information. Then we combine rsdCRP with word co-occurrence modeling and build our short-Text oriented topic evolution model sdTEM. We carry out experimental studies on Twitter dataset. The results demonstrate the effectiveness of our method to monitor social media topic evolution compared to the baseline methods.
Original language | English (US) |
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Title of host publication | 2017 IEEE International Conference on Intelligence and Security Informatics |
Subtitle of host publication | Security and Big Data, ISI 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 119-124 |
Number of pages | 6 |
ISBN (Electronic) | 9781509067275 |
DOIs | |
State | Published - Aug 8 2017 |
Externally published | Yes |
Event | 15th IEEE International Conference on Intelligence and Security Informatics, ISI 2017 - Beijing, China Duration: Jul 22 2017 → Jul 24 2017 |
Other
Other | 15th IEEE International Conference on Intelligence and Security Informatics, ISI 2017 |
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Country | China |
City | Beijing |
Period | 7/22/17 → 7/24/17 |
Keywords
- Social Media Analytics
- Text Mining
- Topic Modeling
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Information Systems
- Information Systems and Management
- Safety, Risk, Reliability and Quality