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Performance Evaluation of Sentiment Analysis on Balanced and Imbalanced Dataset Using Ensemble Approach

Shini George, Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, India, V Srividhya
2022 Indian Journal of Science and Technology  
Methods: At primary level this study uses a novel Synthetic Minority Oversampling Technique (SMOTE) for balancing the dataset and then proposes an ensemble model, named Ensemble Bagging Support Vector  ...  In an imbalanced classification, few minority class instances are unable to provide sufficient information, therefore direct learning from an unbalanced dataset can produce unsatisfactory results.  ...  Methodology The methodology adopted in this analysis, proposes a framework for addressing the issue of class imbalance, as well as an ensemble approach for improving the aspect based sentiment classification  ... 
doi:10.17485/ijst/v15i17.2339 fatcat:5i6qh3kwknglderyehl4ylsk6e

An Empirical Study on Chinese Microblog Stance Detection Using Supervised and Semi-supervised Machine Learning Methods [chapter]

Liran Liu, Shi Feng, Daling Wang, Yifei Zhang
2016 Lecture Notes in Computer Science  
Experiment results show that the method based on ensemble learning and SMOTE2 unbalanced processing with sentiment word features outperforms the best submission result in NLPCC2016 Evaluation Task.  ...  Most of the existing literature are for the debates or online conversations, which have adequate context for inferring the authors' stances.  ...  However, the method based on ensemble learning and SMOTE2 unbalanced processing with sentiment word features could achieve the best result in our experiments which slightly outperforms the best submission  ... 
doi:10.1007/978-3-319-50496-4_68 fatcat:2olevs3g7zeurhdiwnlxhtjpe4

Sentiment Analysis of Emirati Dialects

Arwa A. Al Shamsi, Sherief Abdallah
2022 Big Data and Cognitive Computing  
The results reported that the best accuracy result was 80.80%, and it was achieved when the ensemble model was applied for the sentiment classification of the unbalanced dataset.  ...  Recently, extensive studies and research in the Arabic Natural Language Processing (ANLP) field have been conducted for text classification and sentiment analysis.  ...  Balanced Dataset (Undersampling) (Features Extraction: TF-IDF) Accuracy Recall Precision F-Measure results for sentiment analysis of unbalanced dataset Classification results for sentiment analysis of  ... 
doi:10.3390/bdcc6020057 fatcat:qg6z5wabdnh75n747kxi2grsz4

Evolutionary Optimization of Ensemble Learning to Determine Sentiment Polarity in an Unbalanced Multiclass Corpus

Consuelo V. García-Mendoza, Omar J. Gambino, Miguel G. Villarreal-Cervantes, Hiram Calvo
2020 Entropy  
Finally, there are four different labels, which create the need to adapt current classifications methods for multiclass handling.  ...  issues that multiclass classification and unbalanced corpora pose.  ...  Hence, in this work, the weighting scheme for Twitter sentiment polarity in an unbalanced corpus with four possible polarity values (positive, negative, neutral, and none) is addressed through an optimization  ... 
doi:10.3390/e22091020 pmid:33286789 pmcid:PMC7597113 fatcat:tvgdk7modffhnh7crnfxrhgrnq

GSI-UPM at IberLEF2021: Emotion Analysis of Spanish Tweets by Fine-tuning the XLM-RoBERTa Language Model

Daniel Vera, Oscar Araque, Carlos Angel Iglesias
2021 Annual Conference of the Spanish Society for Natural Language Processing  
Additionally, we also explore the application of several ensemble methods built over the neural language model.  ...  The addressed challenge proposes an emotion classification task of Spanish tweets, categorizing each message into seven emotions.  ...  Table 4 shows that combining all base models through an ensemble generally improves the classification performance when attending to the ensemble methods.  ... 
dblp:conf/sepln/VeraAI21 fatcat:4ylrgtvdancjxnkexpebq6roka

Fine-tuning BERT for Multi-label Sentiment Analysis in Unbalanced Code-Switching Text

Tiancheng Tang, Xinhuai Tang, Tianyi Yuan
2020 IEEE Access  
To process the unbalanced dataset better, the method of data augmentation, undersampling and ensemble learning are used.  ...  The method of using five independent classifications may cause an impossible situation where happiness and sadness exist together.  ... 
doi:10.1109/access.2020.3030468 fatcat:exw64udghvdulir4m5wpqz7dty

Assessing the Influence Level of Food Safety Public Opinion with Unbalanced Samples Using Ensemble Machine Learning

Bo Song, Kefan Shang, Junliang He, Wei Yan, Xiaobo Qu
2022 Scientific Programming  
, FastText, and BERT classification methods into the framework to form an ensemble learner.  ...  Extensive comparison of the proposed method with baseline methods proves the effectiveness of the ensemble learner and the sample generation steps.  ...  will be constructed for an n-class classification problem.5.1.3.  ... 
doi:10.1155/2022/8971882 fatcat:lohfxmieyjeajfqhujxkpqncbi

Improving Sentiment Analysis Through Ensemble Learning of Meta-level Features

Rana Alnashwan, Adrian O'Riordan, Humphrey Sorensen, Cathal Hoare
2016 International Workshop on Knowledge Discovery on the Web  
We propose an ensemble learning approach based on the meta-level features of seven existing lexicon resources for automated polarity sentiment classification.  ...  The ensemble employs four base learners (a Two-Class Support Vector Machine, a Two-Class Bayes Point Machine, a Two-Class Logistic Regression and a Two-Class Decision Forest) for the classification task  ...  First, a set of combinations of sentiment analysis methods and lexicons forms a feature vector for each tweet. Second, an ensemble method uses a supervised approach. 3.1!  ... 
dblp:conf/kdweb/AlnashwanOSH16 fatcat:c2pprlkozfffbhoetkcyrsakxe

An Enhanced Technique for Analyzing Sentiments of Public Reviews - I

2019 International Journal of Inventive Engineering and Sciences  
Bag of Words is the traditional approach for text representation in Sentiment Analysis where text is represented as bag of its words.  ...  The proposed system is to enhance the classification performance of the existing system by applying different classifiers apart from those used in existing system to obtain better results.  ...  selection method as compared with IG for sentiment classification.  ... 
doi:10.35940/ijies.d0926.095619 fatcat:impneawuerczjc6dfg2zjwjqaq

Twitter Sentiment Analysis, 3-Way Classification: Positive, Negative or Neutral?

Mestan Firat Celiktug
2018 2018 IEEE International Conference on Big Data (Big Data)  
In this regard, sentimental polarity detection in social media (e.g. Classification of a tweet as negative or positive or neutral) is highly valuable for certain institutions, organizations.  ...  Online social networks provide great opportunity for propagation of almost any type of information. It's actually much much easier to disseminate an idea/knowledge than previous times.  ...  Especially, ensemble learning methods such as Random Forest and Multi Class Classifier are used for seeing effect of each ensembled classifers learning different classes.  ... 
doi:10.1109/bigdata.2018.8621970 dblp:conf/bigdataconf/Celiktug18 fatcat:z36sif2jgzfbpmsaz2itkes6pe

Survey of Tools and Techniques for Sentiment Analysis of Social Networking Data

Sangeeta Rani, Nasib Singh, Preeti Gulia
2021 International Journal of Advanced Computer Science and Applications  
Keywords-Social networking sites sentiment analysis; twitter sentiment analysis; opinion mining; ensemble classifier; stack based ensemble 222 | P a g e  ...  As the latest advancements, Stack based ensemble, fuzzy based and neural network based classifiers are also implemented to enhance the efficiency of classification.  ...  [20] in their research used multiple sets of features for sentiment classification by using an ensemble classifier.  ... 
doi:10.14569/ijacsa.2021.0120430 fatcat:kccjxxwia5gmfpwixmemza2oqm

Predicting Subjectivity Orientation of Online Forum Threads [chapter]

Prakhar Biyani, Cornelia Caragea, Prasenjit Mitra
2013 Lecture Notes in Computer Science  
Internet users search these forums for different types of information such as opinions, evaluations, speculations, facts, etc.  ...  We demonstrate the effectiveness of our methods on two popular online forums.  ...  For each dataset, we performed experiments using: (i) a single classifier trained on a balanced sample, (ii) a single classifier trained on the entire unbalanced dataset, and (iii) an ensemble of n classifiers  ... 
doi:10.1007/978-3-642-37256-8_10 fatcat:mrcp7h2jpraj5f4ie7v5xbhqle

TwiSE at SemEval-2016 Task 4: Twitter Sentiment Classification [article]

Georgios Balikas, Massih-Reza Amini
2016 arXiv   pre-print
For our final submissions we used an ensemble learning approach (stacked generalization) for Subtask A and single linear models for the rest of the subtasks.  ...  Specifically, we participated in Task 4, namely "Sentiment Analysis in Twitter" for which we implemented sentiment classification systems for subtasks A, B, C and D.  ...  We would also like to thank the anonymous reviewers for their insightful comments.  ... 
arXiv:1606.04351v1 fatcat:uuwwrkqb2rhy3jyzbvtvhyyti4

Transformers Pipeline for Offensiveness Detection in Mexican Spanish Social Media

Victor Gómez-Espinosa, Victor Muñiz-Sanchez, Adrián Pastor López-Monroy
2021 Annual Conference of the Spanish Society for Natural Language Processing  
We proposed a Transformers-based pipeline, consisting on a series of preprocessing steps and the use of an extended corpus, followed by an ensemble of BERT models.  ...  In this paper, we describe the methodology proposed for participating in the MeOffendEs@IberLEF 2021 competition for the Subtask 3: Non-contextual binary classification for Mexican Spanish, which consists  ...  Acknowledgements Gómez-Espinosa thanks CONACYT for the scholarship for Master degree studies with number: 1002761.  ... 
dblp:conf/sepln/Gomez-EspinosaM21 fatcat:ommlmgsxjngwdhbocy7yfmtnay

Implementation of Stacking Ensemble Classifier for Multi-class Classification of COVID-19 Vaccines Topics on Twitter

Rama Jayapermana, Aradea Aradea, Neng Ika Kurniati
2022 Scientific Journal of Informatics  
learners and using Logistic Regression as a meta-learner for the multi-class classification of COVID-19 vaccine topics on Twitter.Result: Based on the evaluation, the proposed Stacking Ensemble Classifier  ...  research.Methods: This study proposes a stacking ensemble classifier method to produce better accuracy by combining Logistic Regression, Random Forest, and Support Vector Machine (SVM) algorithms as first-level  ...  Research [10] proposed a new method with Weighted Classifier Selection and Stacked Ensemble for multilabel classification, resulting in an accuracy value of 0.909 for the MLWSE-L1 model and 0.91 for  ... 
doi:10.15294/sji.v9i1.31648 fatcat:yvdjguay3vhdlblax2nbfzlbfm
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