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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

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Impact factor: 8.15

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Paper Title: Exploration of Sentiment Analysis Using Feature-Based Classification, And Addressing Negations Using NLP
Authors Name: Tripti Anand , Rekha
Unique Id: IJSDR2008041
Published In: Volume 5 Issue 8, August-2020
Abstract: 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.
Keywords: Sentiment Analysis, Sentiment Research, Natural Language Processing, Negative Orientation
Cite Article: "Exploration of Sentiment Analysis Using Feature-Based Classification, And Addressing Negations Using NLP", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 8, page no.319 - 324, August-2020, Available :http://www.ijsdr.org/papers/IJSDR2008041.pdf
Downloads: 000336257
Publication Details: Published Paper ID: IJSDR2008041
Registration ID:192365
Published In: Volume 5 Issue 8, August-2020
DOI (Digital Object Identifier):
Page No: 319 - 324
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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