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Feature Selection Methods in Persian Sentiment Analysis
[chapter]
2013
Lecture Notes in Computer Science
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Up to now as there are few researches conducted on feature selection in sentiment analysis, there are very rare works for Persian sentiment analysis. ...
This paper considers the problem of sentiment classification using different feature selection methods for online customer reviews in Persian language. ...
factors between features and classes improves the performance compared to the other approaches. In our future work we will focus more on sentiment analysis about Persian text. ...
doi:10.1007/978-3-642-38824-8_29
fatcat:ug5m464qufhrllq65lyllluv7a
Flower Pollination Algorithm for Feature Selection in Tweets Sentiment Analysis
2022
International Journal of Advanced Computer Science and Applications
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Machine learning algorithms have been hailed as one of the most efficient approaches for sentiment analysis in recent years. ...
The results demonstrate that the FPA outperforms alternative feature subset selection algorithms. For the FPA, an average improvement in accuracy of 2.7% is seen. ...
However, research on the use of FPA in feature selection problems in sentiment analysis has not yet been conducted. ...
doi:10.14569/ijacsa.2022.0130551
fatcat:ewf45zffincrpofu5wxonrp5ru
A New Feature Selection Method for Sentiment Analysis in Short Text
2018
Journal of Intelligent Systems
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Sentiment analysis is a challenging task in short text, due to use of formal language, misspellings, and shortened forms of words, which leads to high dimensionality and sparsity. ...
The proposed feature selection method outperforms the existing feature selection methods in terms of classification accuracy on the Stanford Twitter dataset. ...
In literature, many researchers developed various feature selection methods for sentiment analysis. ...
doi:10.1515/jisys-2018-0171
fatcat:tajogretbrawzh5tds3x5aikwm
Feature Set Selection for Sentiment Analysis
2021
International Journal for Research in Applied Science and Engineering Technology
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This paper specializes in Sentiment evaluation and use of sentiment Features. In this paper we have created the feature set and given input to svm and result verified for sentiment. ...
Keywords: Sentiment analysis, support vector machine, maximum entropy, with features, without features, artificial intelligence. ...
We conclude that sentiment features method also be solution to sentiment analysis. TABLE I I Dataset consists of 15,000 tweets. ...
doi:10.22214/ijraset.2021.38511
fatcat:z2xdmhvgcbft5pcswop4gtqd7q
Investigation of the Feature Selection Problem for Sentiment Analysis in Arabic Language
2016
Research in Computing Science
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In order to find the optimal number of features and to obtain the best time performance in sentiment analysis, we employ two feature ranking methods (Information Gain based and Chi-Square based) and calculate ...
In this study we design and implement a document-level supervised sentiment analysis system for Arabic context and investigate its performance. ...
Third, observing the performance of the implemented sentiment analysis system using different feature selection techniques and classifiers on the generated datasets. ...
doi:10.13053/rcs-110-1-4
fatcat:ajpg3krl35ge5p2zixnmkz4lpq
A Review of Feature Selection Algorithms in Sentiment Analysis for Drug Reviews
2021
International Journal of Advanced Computer Science and Applications
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This study will also describe the use of metaheuristic algorithms as a feature selection algorithm in sentiment analysis that can help achieve higher accuracy for optimal subset selection tasks. ...
Sentiment analysis technology can be used in the medical domain to help identify either positive or negative issues. ...
A SURVEY OF FEATURE SELECTION USING METAHEURISTIC ALGORITHMS IN SENTIMENT ANALYSIS This section will briefly present feature selection techniques that use metaheuristic algorithms in sentiment analysis ...
doi:10.14569/ijacsa.2021.0121217
fatcat:zjfk7mw36jbk3g22z2gxai5p3q
SA-MSVM: Hybrid Heuristic Algorithm-based Feature Selection for Sentiment Analysis in Twitter
2023
Computer systems science and engineering
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A simulated annealing algorithm searches for relevant features and selects and identifies sentimental terms that customers criticize. ...
The results concluded that SA-MSVM has more potential in sentiment analysis and classification than the existing Support Vector Machine (SVM) approach. ...
SA-MSVM is a hybrid heuristic approach for feature selection. ...
doi:10.32604/csse.2023.029254
fatcat:lourwsxxlzawzog255snadodhy
Interactions Between Term Weighting and Feature Selection Methods on the Sentiment Analysis of Turkish Reviews
[chapter]
2018
Lecture Notes in Computer Science
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Sentiment analysis automatically classifies the opinions, which are expressed in a document, usually as positive or negative. ...
Assigning appropriate weights to features is important to the performance of sentiment analysis so that important features can receive higher weights for the feature vectors. ...
Chi-square (χ2) Chi-square statistic is a commonly used feature selection method in sentiment analysis [3] , [8] . ...
doi:10.1007/978-3-319-75487-1_26
fatcat:er46dvr56fbzhpq54nq5fs52my
Implementation of Feature Selection and balanced random forest for Sentimental Analysis of Text Databases
2017
International Journal of Innovations in Engineering and Technology
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In this paper, we have proposed Correlation based feature selection algorithm with random forest classification. ...
In the event that they're really cheerful, furious or nonpartisan? That is the thing that makes sentiment analysis such a broad and intriguing field. ...
This research paper has been composed with the kind assistance, guidance and support of my department, computer Science who have helped me in this work. ...
doi:10.21172/ijiet.91.03
fatcat:ynxormeqojawhmup4cq2aitiaa
Latent Dirichlet Allocation Feature Extraction with Bio-Inspired Pigeon Feature Selection Technique for Twitter Sentiment Analysis
2020
International Journal of Advanced Trends in Computer Science and Engineering
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Feature selection (FS) is asignificant process for making sentiment analysis (SA). In this study, we propose a wrapper FS algorithm for SA. ...
Feature selection act an important role in structure of machine learning. ...
Pigeon bio inspired feature selection
LITERATURE SURVEY Zhao Jiangqiang et al. ...
doi:10.30534/ijatcse/2020/325942020
fatcat:vwmgsjw4mzhs7mualypkmxrjq4
A Review of Feature Selection and Sentiment Analysis Technique in Issues of Propaganda
2019
International Journal of Advanced Computer Science and Applications
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Feature selection is a dominant side in sentiment analysis due to content of textual has a high measurement classification that can jeopardize SA classification interpretation. ...
This paper presents the various techniques used by previous researchers in issues of propaganda using SA, which include feature selection to remove irrelevant features and sentiment methods to identify ...
A SUMMARY OF FEATURE SELECTION AND SENTIMENT ANALYSIS TECHNIQUES Author
Feature Selection
Sentiment Analysis Techniques
| P a g e www.ijacsa.thesai.org ...
doi:10.14569/ijacsa.2019.0101132
fatcat:m6oqj3lkq5d65ej7ig4ecscotq
A review of feature selection in sentiment analysis using information gain and domain specific ontology
2019
International Journal of Advanced Computer Research
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Two prominent feature selection methods in sentiment analysis are information gain and ontology-based methods. ...
The review of these two methods shows that using the two methods in a two-step approach can overcome their limitations and provide an optimal feature set for sentiment analysis. ...
The second section discusses feature selection in sentiment analysis and the two categories of approaches to feature selection in sentiment analysis. ...
doi:10.19101/ijacr.pid90
fatcat:e4el4tmw4narxkpupcvowdr2r4
Analysis and Evaluation of Two Feature Selection Algorithms in Improving the Performance of the Sentiment Analysis Model of Arabic Tweets
2022
International Journal of Advanced Computer Science and Applications
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In this paper, the Arabic Jordanian sentiment analysis model is proposed through four steps. ...
The high dimensionality of the feature vector is considered to be one of the most popular problems of Arabic sentiment analysis. ...
In this experiment, we compare the accuracy of the most used classifiers in sentiment analysis systems without employing feature selection methods. ...
doi:10.14569/ijacsa.2022.0130683
fatcat:ksmefvgtdbfufmvbauppysvuhe
Sentiment Analysis Using Naive Bayes Algorithm with Feature Selection Particle Swarm Optimization (PSO) and Genetic Algorithm
2021
International Journal of Advances in Data and Information Systems
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The main problem with sentiment analysis is voting and using the best feature options for maximum results. Either, the most widely known classification method is Naive Bayes. ...
That way, in this test, a comparison of feature selection is carried out using Particle Swarm Optimization and Genetic Algorithm to improve the accuracy performance of the Naive Bayes algorithm. ...
CONCLUSION Based on the testing and analysis, it's been concluded that using the selected feature in the Naïve Bayes algorithm for Twitter sentiment analysis can help improve the performance and accuracy ...
doi:10.25008/ijadis.v2i2.1224
fatcat:3dy7ish45zbzxamrmdt4jrfzs4
SENTIMENT ANALYSIS OF MOVIES REVIEWS USING IMPROVISED RANDOM FOREST WITH FEATURE SELECTION
2019
International Journal of Advanced Research in Computer Science
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proposed Gini index feature selection addresses the issues of uneven distribution of prior class probability and global goodness of a feature in two stages. ...
In this paper, based on the drawbacks of random forest, hybrid model using gini index feature selection and balanced random forest is implemented and performance is analysed with the existing techniques ...
doi:10.26483/ijarcs.v10i3.6417
fatcat:ucbe5fw32vdilny5m7ftxjtjza
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