[目的/意義]微博作為人們表達觀點的重要平臺,已成為文本情感分析的一個研究熱點。文章提出一個基于注意力機制的LSTM模型,以華為P10閃存門事件微博相關評論為研究對象,分析網絡用戶對該事件的情感趨向,以驗證該模型的有效性。[方法/過程]引入深度學習理論,使用基于注意力機制的LSTM模型進行情感分析以更好地把握文本中的情感信息,提升情感分類的成功率。[結果/結論]基于注意力機制的LSTM模型是一個有效的模型,在分析較長文本的情感特征時更加準確,比較適合微博這類成段落的文本分析。[局限]對于顏文字、表情包等非文字信息無法進行處理及無法體現詞與詞之間的關系。

[Purpose/significance] As an important platform for people to express their views,micro-blog has gradually become a research hotspot of text sentiment analysis. This paper proposes a LSTM model based on attention mechanism,and takes micro-blog comments of Huawei P10 problem as the research objects to analyze the emotional tendency of network users,which further verifies the effectiveness of this model. [Method/process] The paper introduces the depth learning theory,and uses the LSTM model to carry out emotional analysis in order to better grasp the emotional information in the text and enhance the success rate of emotional classification. [Result/conclusion]The LSTM model is effective,which can be reflected in the accurate analysis of the emotional features of longer texts,especially for paragraph texts of micro-blogs. [Limitations]The proposed model cannot deal with Yan text,facial expressions,and other non-text information,as well as reflect the relationship among words.