Exploring Social Media Trends - A Kannada Dataset Analysis

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Abstract

Platforms for social media are dynamic tools that help ideas spread and develop quickly. This study introduces a novel way of locating popular Kannada-language subjects on social networking sites. This study also involves data preprocessing, feature extraction, and data visualization approaches to reveal underlying patterns and insights using a sizable dataset made up of Kannada text, tweets, hashtags, and news headlines. This method efficiently incorporates both sophisticated Machine Learning models, such as N-grams and word tokenization, and Deep Learning models, including sentence transformers and U-map embeddings. The examination of coherence and silhouette scores is used to validate the models. The main goal of this research is to offer an in-depth analysis of issues that regularly come up in Kannada debates on social media. This enables organizations, researchers, and content producers to make well-informed decisions, comprehend user opinion more thoroughly, and keep up with rapidly changing technological developments. In essence, this study helps provide a thorough understanding of the constantly changing digital ecosystem. © 2023 IEEE.

Year of Conference
2023
Conference Name
2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023
Publisher
Institute of Electrical and Electronics Engineers Inc.
ISBN Number
979-835031341-3 (ISBN)
DOI
10.1109/EASCT59475.2023.10393243
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