Sentiment Analysis of Social Media Data for Product and Brand Evaluation: A Data Mining Approach Unveiling Consumer Preferences, Trends, and Insights
Authors/Creators
- 1. Senior Manager, Department of Software Development and Engineering, Charles Schwab, Co, Texas, US
Description
Sentimental Analysis is an ongoing research field in Text Mining Arena to determine the situation of the market on particular entities such as Products, Services...Etc. This paper is a journal on sentiment analysis in social media that explores the methods, social media platforms used, and their application. It can be called a computational treatment of reviews, subjectivity, and sentiment. Social media contain a large amount of raw data that has been uploaded by users in the form of text, videos, photos, and audio. The data can be converted into valuable information by using sentiment analysis. We aim to collect details like Age, Gender, Education, Marital status, Salary, etc. So there requires data mining techniques like clustering. The Apriori Algorithm is the main algorithm used in our project. The Apriori algorithm is the general algorithm that can be used by developers according to their needs and implemented in their projects.
Files
IJEMR2024140308.pdf
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Additional details
References
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