Paper Details
| Title | Key Aspects of Sentiment Analysis |
|---|---|
| Author | Rajat Verma, Raghvendra Singh |
| Abstract | Sentimentanalysis is a branch dealing in natural language processing (NLP) focused on determining the sentiment determination or opinion expressed in text data. By employing machine learning (ML), statistical analysis, and linguistic techniques, sentiment analysis algorithms classify the underlying sentiment of text as positive, negative, or neutral. This process involves various steps, including text pre-processing, feature extraction, and the application of sentiment classification models. Businesses often use sentiment analysis to gauge public opinion, understand customer feedback, and make data-driven decisions. Its applications extend across social media monitoring, market research, customer service automation, and reputation management, providing valuable insights into people's attitudes and emotions towards products, services, or events. It discusses the areas of application and challenges for sentiment analysis with reference to the work done by the researchers in the past. |
| Keywords | Sentiment analysis, NLP, machine learning, statistical analysis, linguistic techniques |
| Page Number | 22-28 |
| DOI |
View DOI DOI: 10.33804/IJSRI.2021.01.01.https://doi.org/10.5281/zenodo.15666992, |
| Date of Publication | 2024-05-24 |
| Download | Download |