International Journal of Advanced Research in Computer and Communication Engineering

Abstract: A Comparative Study of Sentimental analysis using the NLP and different machine learning and deep learning techniques focuses on analyzing the subjective information conveyed with the expression. This encompasses appraisals, opinions, attitudes or emotions towards a particular subject, individual, or entity. Conventional sentiment analysis solely consider text modalities and the derives sentiment by identifying the semantic relationships between the words in the sentences. Despite this, some expressions, such as exaggeration, sarcasm and humor pose a challenge for the automated detections when conveyed only through the texts. The similar approach can precisely determine the implied sentiment polarities which contain all positive, neutral, Negative sentiment. This research communities can shown significant interest with the topic because of its potential for both the practical application and education related research. With this fact, the paper aims to present all analysis of recent ground breaking research studies which helps the deep learning models in many modalities and works.

Keywords: Sentiment Analysis, Deep Learning, Emotion Recognition, Opinion Mining, Sarcasm and Humor Detection.

Downloads: | DOI: 10.17148/IJARCCE.2025.14920