Exploration of Sentiment Analysis Using Feature-Based Classification, And Addressing Negations Using NLP
Sentiment Analysis, Sentiment Research, Natural Language Processing, Negative Orientation
Sentiment analysis is techniques of text analysis which detect text polarity automatically. Sentiment research is often called impression mining and is one of the NLP's (Natural Language Processing) main activities. Study of the emotions has attracted tremendous popularity in recent years. Individuals are supposed to build a mechanism capable of defining and classifying thoughts or emotions as expressed in an online document. Consumers frequently face the trade-off in purchasing choices and nowadays if you choose to purchase a consumer good you choose customer feedback and conversation regarding the product in online forums on the internet. When taking their purchasing choices, often customers use feedback shared by other users. People have a propensity to speak out about various institutions. Opinion mining has grown in popularity as a result. Sentiment Analysis assesses how this viewpoint shared regarding the object has a favorable or a negative orientation. Consumers ought to determine which subset of knowledge they choose to use. The method by which contextual meaning is defined and derived from raw data is known as sentiment analysis. An effective method for predicting feelings may enable one to collect views from the internet and predict the tastes of online consumers, which could prove useful for economic or marketing research. There are so far few specific problems that predominate in this research community, namely, classification of emotions, feature-based classification, and addressing negations. This paper provides a study of the approaches and strategies that exist in the area of sentiment analysis, and obstacles.
"Exploration of Sentiment Analysis Using Feature-Based Classification, And Addressing Negations Using NLP", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 8, page no.319 - 324, August-2020, Available :https://ijsdr.org/papers/IJSDR2008041.pdf
Volume 5
Issue 8,
August-2020
Pages : 319 - 324
Paper Reg. ID: IJSDR_192365
Published Paper Id: IJSDR2008041
Downloads: 000347189
Research Area: Engineering
Country: -, -, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
