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- 59 creator hongyun-bao.
- 59 creator qiudan-li.
- 59 creator shuangyong-song.
- 59 type InProceedings.
- 59 label "Detecting Dynamic Association among Twitter Topics".
- 59 sameAs 59.
- 59 abstract "Over the last few years, Twitter is increasingly becoming an important source of up-to-date topics about what is happening in the world. In this paper, we propose a dynamic topic association detection model to discover relations between Twitter topics, by which users can gain insights into richer information about topics of interest. The proposed model utilizes a time constrained method to extract event-based spatio-temporal topic association, and constructs a dynamic temporal map to represent the obtained result. Experimental results show the improvement of the proposed model compared to static spatio-temporal method and co-occurrence method.".
- 59 hasAuthorList authorList.
- 59 isPartOf proceedings.
- 59 isPartOf proceedings.
- 59 keyword "Burst detection".
- 59 keyword "Dynamic temporal map".
- 59 keyword "Topic association".
- 59 keyword "Twitter".
- 59 title "Detecting Dynamic Association among Twitter Topics".