Sentiment Analysis-Enhancements and Applications
| Autor: | Saarthak Agarwal, Aayush Gupta, Anant Gandhi, Shamin Chokshi, K. Saravanakumar |
|---|---|
| Přispěvatelé: | Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) |
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science 2277-3878 Management of Technology and Innovation Sentiment analysis General Engineering 100.1/ijrte.A1409059120 Artificial intelligence Sentiment Analysis Lexicon Support vector machine Regression business computer.software_genre computer Natural language processing |
| Zdroj: | International Journal of Recent Technology and Engineering (IJRTE). 10:56-70 |
| ISSN: | 2277-3878 |
| Popis: | The concept of Natural Language Processing that deals with problems of identifying the sentiment from the voice or text of a speaker or writer and then use that analysis further for making predictions, market survey, customer service, product satisfaction, precision targeting etc. is called Sentiment analysis. From one viewpoint, it is an abstract evaluation of something dependent on close to home observational experience. It Is mostly established in target realities and incompletely governed by feelings. Then again, a sentiment can be deciphered as a kind of measurement in the information in regards to a specific subject. It is a lot of markers that mix present a point of view, i.e., perspective for the specific issue. So as to enhance the accuracy of sentiment analysis/classification, it is imperative to appropriately recognize the semantic connections between the various words and phrases that are describing the subject or aspect. This can be done by applying semantic analysis with a syntactic parser and supposition vocabulary. This research will discuss different sets of approaches for application or domain specific problems and then compare them to obtain the best possible approaches to the problem of sentiment analysis. |
| Databáze: | OpenAIRE |
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