Abstract

With the rapid development of the Internet economy, the online transaction volume of e-commerce platforms has soared, and the purchase experience shared by users has become particularly important. How to quickly and effectively extract the required information from a large number of user reviews plays an important role in the decision-making of both consumers and businesses. This article conducts sentiment analysis on JD business platform Huawei mobile phone user comment information. First, this paper use crawler methods to collect user evaluation text information, and perform data preprocessing such as deduplication and cleaning of the collected raw data; then perform word segmentation on the processed text content, and filter stop words and worthless words; use the method based on emotional dictionary matching to analyze the sentiment tendency of the text. Finally, using the LDA topic analysis model, LDA topic analysis is performed on the sentiment classification text, and the topic words are extracted to obtain valuable internal information, and reasonable marketing strategies are proposed for the business.

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