【目的】識別網絡輿情中的觀點主題。【方法】通過輿情信息內容、用戶關系、用戶行為三個方面的4個維度(時間維、用戶維、內容維、觀點維)的關聯,構建微博輿情觀點主題識別模型。【結果】提出包括輿情網絡構建、觀點主題抽取及聚類、"用戶–所屬觀點主題"2-模網絡構建、觀點主題演化分析4部分的網絡輿情觀點主題識別方法體系,實驗結果證明該方法體系可有效識別網絡輿情中的觀點主題。【局限】用戶屬性對觀點主題識別的影響有待進一步考慮。【結論】基于社會網絡視角,利用LDA主題模型,可多方面、多維度地識別網絡輿情觀點主題。

[Objective] This paper aims to identify the topics of online public opinion. [Methods] We constructed a model to extract public opinion based on the information content of the Weibo posts, the relationship among the users, and user behaviors. [Results] We built a public opinion network, extracted and clustered relevant topics, constructed a two-mode network of "user-topic" and evolution of the opinion topics. The proposed method could identify topics of online public opinion effectively. [Limitations] The influence of users' attributes on topic identification needed to be investigated. [Conclusions] We could identify the topics of online public opinion based on the social network analysis with the help of LDA model.