Emotion and Sentiment Analysis Using Lexical and Social Media Data with NLP Techniques

Emotion and Sentiment Analysis Using Lexical and Social Media Data with NLP Techniques

Authors- V. Vinoth, Dr. P. Kavitha

Abstract-This study presents a hybrid approach to sentiment and emotion analysis by combining lexical rule- based methods and real-time data mining from social media platforms. The primary focus is on the use of Natural Language Processing (NLP) techniques such as tokenization, stop-word removal, lemmatization, and lexicon-based mapping to detect emotions and polarity within a given text. The methodology includes analyzing structured speeches and unstructured Twitter content to demonstrate the adaptability of emotion detection across content types. This paper aims to provide an efficient and interpretable framework for both academic and real-world sentiment monitoring applications.

DOI: /10.61463/ijset.vol.13.issue3.128