Authors :
Dr. M.S. Chaudhari; Ms. Nupur Banode; Kaushal Lande; Ankita Nademwar; Siddhi Ghosekar; Dnyanesh Lambat; Sagar Lende
Volume/Issue :
Volume 8 - 2023, Issue 11 - November
Google Scholar :
https://tinyurl.com/yfbv3c3e
Scribd :
https://tinyurl.com/49b3bwst
DOI :
https://doi.org/10.5281/zenodo.10200419
Abstract :
The research paper investigates the effectiveness
of machine learning methods in predicting human emotions
from text data through sentiment analysis. It reviews
existing literature, explores diverse datasets, and applies
various machine learning models to predict emotions
accurately. Results demonstrate the success of these models,
highlighting their real-world applications in marketing,
mental health analysis, and user experience enhancement.
The study concludes by outlining future research directions
for improved emotion prediction using sentiment analysis,
contributing to the advancement of understanding and
utilizing emotional states derived from text.
Keywords :
Sentiment Analysis, Polarity, Bag of words, SentiWordNet.
The research paper investigates the effectiveness
of machine learning methods in predicting human emotions
from text data through sentiment analysis. It reviews
existing literature, explores diverse datasets, and applies
various machine learning models to predict emotions
accurately. Results demonstrate the success of these models,
highlighting their real-world applications in marketing,
mental health analysis, and user experience enhancement.
The study concludes by outlining future research directions
for improved emotion prediction using sentiment analysis,
contributing to the advancement of understanding and
utilizing emotional states derived from text.
Keywords :
Sentiment Analysis, Polarity, Bag of words, SentiWordNet.
