JOURNAL ARTICLE

Sentiment Analysis of Customer Reviews Using Machine Learning and Natural Language Processing Methods

Doğan, EmircanBalkancı, SelenayÇırakoğlu, EcenazAltun, Erdem

Year: 2024 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

The study aims to design a system using natural language processing (NLP) methods from machinelearning for sentiment analysis via Twitter. This system will classify comments from customers whohave used airline services, to analyze and categorize their sentiments. By analyzing the comments ofcustomers who have used airline services, the aim is to improve the experiences of both customers andcompanies. The selected tweets will be classified as positive, negative, or neutral, and sentiment analysiswill be conducted based on the results. Additionally, efforts will be made to predict which departmentwithin a company a comment is related to. Data will be obtained from the social media platform Twitter, and a sentiment analysis report will be produced using NLP. The Twitter API will be used for the appli-cation, leveraging Python libraries that utilize NLP methods.

Keywords:
Sentiment analysis Categorization Python (programming language) Social media Natural language Chatbot

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Topics

Poetry Analysis and Criticism
Social Sciences →  Arts and Humanities →  Literature and Literary Theory
Caribbean history, culture, and politics
Social Sciences →  Social Sciences →  Cultural Studies
Themes in Literature Analysis
Social Sciences →  Arts and Humanities →  Literature and Literary Theory

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