Natural Language Processing Techniques for Social Media Sentiment Analysis DOI
Mohamed Hammad, Wesam Ahmed

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 33 - 62

Published: April 30, 2025

This Chapter presents a comprehensive examination of Natural Language Processing [NLP] techniques for sentiment analysis in social media contexts, addressing the unique challenges and opportunities presented by user-generated content on platforms. We trace evolution from early lexicon-based approaches through modern transformer architectures, highlighting technological advancements that have revolutionized our ability to understand analyze sentiment. The provides detailed insights into advanced NLP techniques, preprocessing methodologies, architectural considerations implementing robust systems. also explore evaluation frameworks metrics assessing system performance, along with crucial implementation real-world applications. concludes an emerging trends future directions, including privacy-preserving ethical analysis.

Language: Английский

Natural Language Processing Techniques for Social Media Sentiment Analysis DOI
Mohamed Hammad, Wesam Ahmed

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 33 - 62

Published: April 30, 2025

This Chapter presents a comprehensive examination of Natural Language Processing [NLP] techniques for sentiment analysis in social media contexts, addressing the unique challenges and opportunities presented by user-generated content on platforms. We trace evolution from early lexicon-based approaches through modern transformer architectures, highlighting technological advancements that have revolutionized our ability to understand analyze sentiment. The provides detailed insights into advanced NLP techniques, preprocessing methodologies, architectural considerations implementing robust systems. also explore evaluation frameworks metrics assessing system performance, along with crucial implementation real-world applications. concludes an emerging trends future directions, including privacy-preserving ethical analysis.

Language: Английский

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