International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Multilingual Sentimental Analysis of You Tube Comments

Author(s) Chikka Krishnappa T K, Nihal B Nayaka, Pavana B C, Shilpashree P, Shreyas U V
Country India
Abstract The increasing use of multilingual platforms like YouTube has created a demand for effective sentiment analysis tools capable of processing diverse languages. This paper presents a comprehensive approach to multilingual sentiment analysis, focusing on English, Kannada, Hindi, Telugu comments. The study incorporates advanced Natural Language Processing (NLP) techniques, such as tokenization, stemming, and TF-IDF vectorization, alongside machine learning algorithms like Logistic Regression, Random Forest, and Linear SVC. The system employs a modular architecture, including language detection, feature extraction, and sentiment classification. Results demonstrate the model's ability to identify emotions with high accuracy, contributing to content creators' and marketers' efforts to understand audience engagement. Challenges like code-switching and limited language resources are discussed, with potential enhancements proposed to improve inclusivity and scalability.
Keywords Multilingual Sentiment Analysis, Natural Language Processing, YouTube Comments, Kannada, English, Hindi, Telugu Emotion Classification, Machine Learning, Code-Switching, Multilingual NLP, Sentiment Visualization.
Field Engineering
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-02-05
Cite This Multilingual Sentimental Analysis of You Tube Comments - Chikka Krishnappa T K, Nihal B Nayaka, Pavana B C, Shilpashree P, Shreyas U V - IJFMR Volume 7, Issue 1, January-February 2025.
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E-ISSN 2582-2160
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