摘要
As microblogs have become one of the most important social platforms, it is considered to be extremely valuable to extract user interests hidden behind microblogs. In this paper, we introduce a framework, which is built on the improved TextRank model, to analyze the personal interest of microblog users. In the framework, we first create a catalog of user interests basing on hot tags of Sina Weibo, the largest microblog system in China. And then TF-IDF factor is used in TextRank model to deal with pre-processed microblog contents. After ranking and mapping all extracted words into user interests catalog established previously, we get corresponding user interests tags and a user interests model. Experimental results on Sina Weibo data imply that the proposed framework outperforms other existing methods.
延伸閱讀
- 周勝（2022）。Research on Microblog User Clustering from a Cognitive Perspective。傳播與社會學刊，(59)，177-209。https://doi.org/10.30180/CS.202201_(59).0008
- Yu, C. F. (2015). Mining User Interests from Social Media: Fusion of Textual and Visual Features [master's thesis, National Tsing Hua University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0016-1802201617065162
- Wang, T. Y. (2014). Inferring User Interests on Microblog based on Social Contributed Contextual Approach [master's thesis, National Tsing Hua University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0016-2912201413550810
- Jia, X. (2015). Mining User Interests from Social Media Based on Social Group Content Analysis [master's thesis, National Tsing Hua University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0016-0312201510311090
- 梁哲瑋（2010）。Mining Topic Interests of Users from Micro-blogs based on Wikipedia〔碩士論文，國立臺灣師範大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0021-1610201315183188