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Feature Selection Methods in Persian Sentiment Analysis [chapter]

Mohamad Saraee, Ayoub Bagheri
2013 Lecture Notes in Computer Science  
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

Muhammad Iqbal Abu Latiffi, Mohd Ridzwan Yaakub, Ibrahim Said Ahmad
2022 International Journal of Advanced Computer Science and Applications  
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

H. M. Keerthi Kumar, B. S. Harish
2018 Journal of Intelligent Systems  
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

Ganesh K. Shinde
2021 International Journal for Research in Applied Science and Engineering Technology  
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

Ahmed Nasser, Kıvanç Dinçer, Hayri Sever
2016 Research in Computing Science  
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

Siti Rohaidah Ahmad, Nurhafizah Moziyana Mohd Yusop, Afifah Mohd Asri, Mohd Fahmi Muhamad Amran
2021 International Journal of Advanced Computer Science and Applications  
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

C. P. Thamil Selvi, R. PushpaLaksmi
2023 Computer systems science and engineering  
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]

Tuba Parlar, Selma Ayşe Özel, Fei Song
2018 Lecture Notes in Computer Science  
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  
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

Kasthuri S.
2020 International Journal of Advanced Trends in Computer Science and Engineering  
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

Siti Rohaidah Ahmad, Muhammad Zakwan, Nurlaila Syafira, Nurhafizah Moziyana, Suhaila Ismail
2019 International Journal of Advanced Computer Science and Applications  
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  ... 
doi:10.14569/ijacsa.2019.0101132 fatcat:m6oqj3lkq5d65ej7ig4ecscotq

A review of feature selection in sentiment analysis using information gain and domain specific ontology

Ibrahim Said Ahmad, Azuraliza Abu Bakar, Mohd Ridzwan Yaakub
2019 International Journal of Advanced Computer Research  
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

Maria Yousef, Abdulla ALali
2022 International Journal of Advanced Computer Science and Applications  
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

Abi Rafdi, Herman Mawengkang Herman, Syahril Efendi
2021 International Journal of Advances in Data and Information Systems  
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


Er.Manpreet Kaur, M.Tech Scholar, Department of Computer Science & Engineering, Amritsar College of Engineering & Technology, Amritsar, Punjab, India
2019 International Journal of Advanced Research in Computer Science  
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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