【目的】融合社會網絡分析與影響力擴散模型,提出一種識別網絡意見領袖的改進方法,以更好地引導網絡輿情發展。【方法】從社會網絡分析出發,在分析網絡意見領袖重要指標的基礎上,引入用戶影響力擴散模型,從意見領袖影響范圍和影響深度兩方面提出優化的意見領袖發現模型。【結果】與單一的中心性分析模型和語義相似度模型對比,融合兩種方法的綜合意見領袖識別模型進一步優化了意見領袖排序結果,與原始微博數據更為一致。【局限】研究語料來源于"轉基因食品"話題,具有一定的領域局限性。【結論】本文模型從度的量的關系和度的權重語義距離兩方面發現意見領袖,效果更為明顯。

[Objective] This paper tries to identify Weibo opinion leaders with the help of social network analysis and influence diffusion model. [Methods] First, we analyzed the opinion leaders’ characteristics based on the social network analysis. Then we optimized the existing influence diffusion model from the perspectives of impact scope and extent. Finally, we applied the new model to find opinion leaders. [Results] Compared with the models built on centrality analysis or semantic similarity, the optimized model obtained better ranking for opinion leaders, which was consistent with the Weibo data. [Limitations] Only examined the proposed method with data on GMO foods. [Conclusions] The proposed model could effectively identify the Weibo opinion leaders.