A Comprehensive Survey on Sentiment Analysis in Twitter Data

A Comprehensive Survey on Sentiment Analysis in Twitter Data

Hema Krishnan, M. Sudheep Elayidom, Santhanakrishnan T.
Copyright: © 2022 |Pages: 22
DOI: 10.4018/IJDST.300352
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Abstract

The literature scrutinizes on diverse techniques that are associated with sentiment analysis in twitter data. It reviews several research papers and states the significant analysis. Initially, the analysis depicts various schemes that are contributed in different papers. Subsequently, the analysis also focuses on various features and it also analyses the sentiment analysis in twitter data that is exploited in each paper. Furthermore, this paper provides the detailed study regarding the performance measures and maximum performance achievements in each contribution. Finally, it extends the various research issues which can be useful for the researchers to accomplish further research on sentiment analysis in twitter data.
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1. Introduction

Table 1.
Nomenclature
AbbreviationDescription
SASentiment Analysis
SVMSupport Vector Machine
BOWBag-Of-Words
SVNSSingle Valued Neutrosophic Set
TANTree Augmented Naive Bayes
NLPNatural Language Processing
TDMTerm Document Matrix
SVCSupport Vector Classifier
MVOMulti-Verse Optimizer
TSATwitter Sentiment Analysis
RNNRecurrent Neural Network
CSKCuckoo Search And K-Mean
VAAVoting Advice Applications
PIParticipa Intelligence
URLUniform Resource Locator
MRNSMulti Refined Neutrosophic Set
CNNConvolutional Neural Network
TRINSTriple Refined Indeterminate Neutrosophic Set
LDALatent Dirichlet Allocation
SVRSupport Vector Regression
    DHSDaily Happiness Sentiment
FEARSFinancial and Economic Attitudes Revealed By Search
MF-DCCAMultifractal Detrended Cross-Correlation Analysis
TS-LDATrend Sensitive-LDA
MSEMean Square Error
RFRandom Forest
RCB-LDAReason Candidate and Background LDA
DCNNDeep Convolutional Neural Network
DJIADow Jones Industrial Average
DTDecision Trees
CAARIAClass Association and Attribute Relevancy Based Imputation Algorithm
NLTKNatural Language Toolkit
LSTMLong Short-Term Memory
FB-LDAForeground and Background LDA
EDErectile Dysfunction
LSLeast Squares
SIRAStart-Up Initiative Response Analysis
CAConjunction Analysis
AUCArea Under Curve
DAData Augmentation
TPTrue Positive
CHPCombined Heat and Power
LRLogistic Regression
ADRAdverse Drug Reactions
FPRFalse Positive Rate
PMIPunctuation Mark Identification
NBNaïve Bayes
RMTRandom Matrix Theory
ANNArtificial Neural Network
PEPremature Ejaculation
PCCPearson Correlation Coefficients
WAPEWeighted Absolute Percentage Error
MAPEMean Absolute Percentage Error
NMAENormalized Mean Absolute Error

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