中圖分類號： TP391.1
文獻標識碼： A
DOI： 10.19358/j.issn.2096-5133.2021.01.008
引用格式： 李宸嚴，劉繼。 基于注意力與Bi-LSTM混合算法的車企輿情情感分析[J].信息技術(shù)與網(wǎng)絡(luò)安全，2021，40（1）：45-49.

Public opinion sentiment analysis of automobile enterprises based on attention mechanism and Bi-LSTM

Abstract： With the advent of the era of big data, online public opinion has a significant impact on consumer sentiment analysis and business marketing strategy. How to use big data technology to improve the efficiency of sentiment analysis of automobile enterprises′ public opinion has been widely concerned by text mining researchers. Aiming at the long-term dependence of traditional RNN in long text classification, a hybrid classification algorithm（At-BI-LSTM） combining attention mechanism and Bi-LSTM is proposed. The algorithm uses Bi-LSTM to analyze the emotion of online reviews of automobile enterprises, and introduces attention mechanism to calculate the contribution weight of different words to the sentiment of comments, so as to reduce the influence of irrelevant words in long text on classification results. Experiments show that At-BI-LSTM algorithm achieves better classification effect than Naive Bayes, SVM and LSTM.

Key words : attention mechanism；Bi-LSTM；public opinion of car enterprises；emotion classification