电影评论的情感分析:朴素贝叶斯分类器与基于规则方法的比较研究

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI:10.1109/ICITIIT51526.2021.9399610

Vihaan Nama, Vinay V. Hegde, B. S. Satish Babu

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引用次数: 3

摘要

电影评论对于告诉观众一部电影是否值得一看至关重要。它们可以分为文本影评和非文本影评。非文本的电影评论(星级)给用户提供了关于电影如何表现的信息，而文本的电影评论给用户提供了关于电影正面和负面方面的更详细的图片。情感分析是利用自然语言处理、文本分析、生物识别和计算语言学来识别、量化、提取和有效研究以文本形式给出的状态和主观信息。本文旨在使用朴素贝叶斯算法对电影评论进行情感分析，并将结果与使用AFINN-111情感词典的基于规则的方法进行比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Sentiment Analysis of Movie Reviews: A Comparative Study between the Naive-Bayes Classifier and a Rule-based Approach

Movie reviews are vital in telling the viewer whether a movie is worth watching or not. They can be classified into textual and non-textual movie reviews. While non-textual movie reviews (stars) give the user information as to how the movie fairs, textual movie reviews give the user a more detailed picture on the positive and negative aspects of the movie. Sentiment Analysis is the use of natural language processing, text analysis, biometrics and computational linguistics to identify, quantify, extract and effectively study states and subjective information given in textual format. This paper aims to conduct sentiment analysis of reviews of movies by using the Naive-Bayes algorithm and compare the results to that of a Rule-Based Approach using the AFINN-111 sentiment dictionary.

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2021 International Conference on Innovative Trends in Information Technology (ICITIIT)

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