"Hot and Hot"LDA Theme Mining Based on Emotional Classification
Taking user reviews from Douban Movie website regarding the film"Hot and Spicy"as the data source,sentiment classification and LDA(Latent Dirichlet Allocation)topic model was employed for an in-depth analysis of the movie reviews.Firstly,data was preprocessed,which included deduplication,word segmentation,construction of a stop word list,matching with a sentiment lexicon and correction of sentiment tendencies,categorizing the reviews into positive and negative sentiments.Mapping the positive and negative emotional word clouds reveals the audience's positive comments on the display of female power,the integration of inspirational elements,and the expression of humor in the film,as well as negative feedback on the lack of plot innovation and excessive marketing publicity.Further LDA topic analysis identifies"Inspirational Life"and"Self-Reconstruction"as positive themes,and"Over-Marketing"and"Plagiarism and Remakes"as negative themes.The results provide valuable audience insights for film production,suggestions are proposed that production teams should focus on plot innovation,authentic marketing,in-depth character portrayal,and cultural dissemination in future works to enhance the artistic value and market competitiveness of the film.
NETL
NSTL
万方数据
