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Simpler is better? Lexicon-based ensemble sentiment classification beats supervised methods

Lukasz Augustyniak, Tomasz Kajdanowicz, Piotr Szymanski, Wlodzimierz Tuliglowicz, Przemyslaw Kazienko, Reda Alhajj, Boleslaw Szymanski
2014 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)  
It has been shown in this paper that simplistic Bag of Words (BoW) lexicon methods for sentiment polarity assignment with ensemble classifiers are much faster than a supervised approach to sentiment classification  ...  BoW methods also proved to be efficient and fast across all examined datasets.  ...  Hence, the idea is to improve the efficiency of lexicon-based method by use of several lexicons, and by assembling classification provided by these simple and fast methods.  ... 
doi:10.1109/asonam.2014.6921696 dblp:conf/asunam/AugustyniakKSTKAS14 fatcat:kznf2x7wdfdsrl6qqbj35u354m

Review of Factors Affecting Efficiency of Twitter Data Sentiment Analysis

Sangeeta Sangeeta, Department of Computer Science & Application with Maharishi Dayanand University, Rohtak, India, Nasib Singh Gill
2020 Journal of clean energy technologies  
Consideration of these factors can be very beneficial while designing an efficient classification model for twitter sentiment analysis.  ...  The survey also focuses on various metrics used for representation of sentiment analysis result and their relevance.  ...  Sangeeta conducted review and research work; Nasib Singh Gill analyzed the data and work; Sangeeta wrote the paper; all authors had approved the final version.  ... 
doi:10.7763/ijcte.2020.v12.1263 fatcat:s5rrbykzlfel7fvspzfhvfbeoe

Hybrid Model using Stack-Based Ensemble Classifier and Dictionary Classifier to Improve Classification Accuracy of Twitter Sentiment Analysis

Sangeeta Rani
2020 International Journal of Emerging Trends in Engineering Research  
In the present research, a hybrid model based on stack based ensemble classifiers and dictionary based classifier is used for tweet classification as positive and negative.  ...  To enhance accuracy of classification, sentiment score retrieved from dictionary based classifier is added to the feature vector to get enhanced feature set and the hybrid stack based ensemble model is  ...  [29] used an ensemble of KNN and NB for sentiment classification. Results are further improved to an accuracy of 95% by using of KNN, NB and SVM based ensemble. J. Prusa et al.  ... 
doi:10.30534/ijeter/2020/02872020 fatcat:z6k4ia4bdre4pj7g6j4herm4rm

Intelligent Hybrid Feature Selection for Textual Sentiment Classification

Jawad Khan, Aftab Alam, Youngmoon Lee
2021 IEEE Access  
The sentiment features subset is then selected employing a fast and simple rank-based ensemble of multiple filters feature selection method.  ...  To address these concerns, we propose an Intelligent Hybrid Feature Selection for Sentiment Analysis (IHFSSA) based on ensemble learning methods.  ...  CLASSIFICATION ALGORITHMS AND ENSEMBLE LEARNING METHOD In this section, we briefly discuss the classification algorithms with ensemble learning method for sentiment classification.  ... 
doi:10.1109/access.2021.3118982 fatcat:etece4olsrdjdojpewvpt53jbu

Comprehensive Study on Lexicon-based Ensemble Classification Sentiment Analysis

Łukasz Augustyniak, Piotr Szymański, Tomasz Kajdanowicz, Włodzimierz Tuligłowicz
2015 Entropy  
Afterwards, we use ensemble classification to improve the overall accuracy of the method.  ...  We compare 37 methods (lexicons, ensembles with lexicon's predictions as input and supervised learners) applied to 10 Amazon review data sets and provide the first statistical comparison of the sentiment  ...  The authors would like to acknowledge the help of Joanna Kaczmar in constructing the frequentiment measure and implementing Python code.  ... 
doi:10.3390/e18010004 fatcat:xnzcxeafbnhd5gcb4wvukkcxue

The Today Tendency of Sentiment Classification [chapter]

Vo Ngoc Phu, Vo Thi Ngoc Tran
2018 Artificial Intelligence - Emerging Trends and Applications  
Lexicon-based approaches The lexicon-based approaches are comprised of multiple approaches, both dictionary-based and corpus-based.  ...  The today tendency of the sentiment classification is as follows: (1) Processing many big data sets with shortening execution times (2) Having a high accuracy (3) Integrating flexibly and easily into many  ...  The authors of [11] propose a lexicon-based approach to sentiment classification of Twitter posts.  ... 
doi:10.5772/intechopen.74930 fatcat:w3wqlxtuzrba7gkqcj5og6w45a

Survey and Analysis of Recent Sentiment Analysis Schemes Relating to Social Media

Osamah Ali Mohammed Ghaleb, Anna Saro Vijendran
2016 Indian Journal of Science and Technology  
Methods/ Statistical Analysis: Extraction of the information from the web, classification and prediction of the sentiment polarity is a complex process which performed through various approaches like Part-Of-Speech  ...  Objectives: Sentiment analysis from the online web and social media contents is an important research and applications field for the organizations, businesses, and political and social life issues; in  ...  SACI is a lexicon-based unsupervised method that extracts collective sentiments without being concerned with individual classifications.  ... 
doi:10.17485/ijst/2016/v9i41/97767 fatcat:447w5xhaunaavfxgbitggsjhqi

Analysis of Various Sentiment Classification Techniques

Vimalkumar B., Bhumika M.
2016 International Journal of Computer Applications  
Sentiment analysis is an ongoing research area in the field of text mining.  ...  This paper presents recent updates on papers related to classification of sentiment analysis of implemented various approaches and algorithms.  ...  Lexicon based approach is further divided into two category namely dictionary based and corpus based approach.  ... 
doi:10.5120/ijca2016909259 fatcat:r32jcbc26zg5lc7qj6mzenmk4e

Ensemble Approach for Twitter Sentiment Analysis

Dimple Tiwari, Ambedkar Institute of Advanced Communication Technologies and Research Govt. of NCT of Delhi, India, Nanhay Singh
2019 International Journal of Information Technology and Computer Science  
Due to enlargement of social network and online marketing websites.  ...  So, for improving the accuracy of these algorithms two ensemble methods AdaBoost and Extra Tree are applied.  ...  Combined approach of rule-based classifier and supervised learning can use for sentiment analysis. And the SVM is trained on dependency and the feature of sentiment lexicon [21] .  ... 
doi:10.5815/ijitcs.2019.08.03 fatcat:27bxtr4bqbe2rp4t7wfwvmkieu

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

Georgios Balikas, Massih-Reza Amini
2016 arXiv   pre-print
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.  ...  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.  ...  Acknowledgments We would like to thank the organisers of the Task 4 of SemEval 2016, for providing the data, the guidelines and the infrastructure.  ... 
arXiv:1606.04351v1 fatcat:uuwwrkqb2rhy3jyzbvtvhyyti4

COVID-19 Vaccination-Related Sentiments Analysis: A Case Study Using Worldwide Twitter Dataset

Aijaz Ahmad Reshi, Furqan Rustam, Wajdi Aljedaani, Shabana Shafi, Abdulaziz Alhossan, Ziyad Alrabiah, Ajaz Ahmad, Hessa Alsuwailem, Thamer A. Almangour, Musaad A. Alshammari, Ernesto Lee, Imran Ashraf
2022 Healthcare  
To evaluate the performance of the different lexicon-based methods, different machine and deep learning models are studied.  ...  In addition, for sentiment classification, the proposed ensemble model named long short-term memory-gated recurrent neural network (LSTM-GRNN) is a combination of LSTM, gated recurrent unit, and recurrent  ...  This research was supported by the Florida Center for Advanced Analytics and Data Science funded by Ernesto.Net (under the Algorithms for Good Grant).  ... 
doi:10.3390/healthcare10030411 pmid:35326889 pmcid:PMC8951387 fatcat:sj3mkiw3hjeahn5rzuhxmxgbrq

The State-of-the-Art in Twitter Sentiment Analysis

David Zimbra, Ahmed Abbasi, Daniel Zeng, Hsinchun Chen
2018 ACM Transactions on Management Information Systems  
Despite this attention, state-of-the-art Twitter sentiment analysis approaches perform relatively poorly with reported classification accuracies often below 70%, adversely impacting applications of the  ...  To assess the state-of-the-art in Twitter sentiment analysis, we conduct a benchmark evaluation of 28 top academic and commercial systems in tweet sentiment classification across five distinctive data  ...  analysis, and event detection case study.  ... 
doi:10.1145/3185045 fatcat:fzpm7xhkyvd2newi2yp3gze7gm

Collaborative Classification Approach for Airline Tweets Using Sentiment Analysis

M.Veera Kumari
2021 Turkish Journal of Computer and Mathematics Education  
This paper develop the different classification techniques to improve accuracy for sentiment analysis.  ...  Classification methods are Random forest(RF), Logistic Regression(LR), K-Nearest Neighbors(KNN), Naïve Baye's(NB), Decision Tree(DTC), Extreme Gradient Boost(XGB), merging of (two, three and four) classification  ...  viii) Extreme Gradient Boosting(XGB): XGBoost is an operation of gradient boosted decision trees arranged for fast accurate and performance.  ... 
doi:10.17762/turcomat.v12i3.1639 fatcat:7hlbs6kkefftvp7jozmbkb3hfi

UIUC at SemEval-2018 Task 1: Recognizing Affect with Ensemble Models

Abhishek Avinash Narwekar, Roxana Girju
2018 Proceedings of The 12th International Workshop on Semantic Evaluation  
The baseline considered was an SVM (Support Vector Machines) model with linear kernel on the lexicon and embedding based features.  ...  We used an ensemble of diverse models, including random forests, gradient boosted trees, and linear models, corrected for training-development set mismatch.  ...  Our system comprised an ensemble trained on lexicon based and embedding based features.  ... 
doi:10.18653/v1/s18-1057 dblp:conf/semeval/NarwekarG18 fatcat:trboipclirdlrmii2pwj4fla3q

Content-Specific Unigrams and Syntactic Phrases to Enhance Senti Word Net Based Sentiment Classification

Muhammad Latif, Usman Qamar, Abdul Wahab Muzaffar
2015 International Journal of Machine Learning and Computing  
Index Terms-Content specific features, lexicon based classification, sentiment classification, Senti word net.  ...  Use of content specific unigrams and syntactic phrases along with sentiment features ensures consistency in the classification while enhancing the performance paradigm.  ...  Index Terms-Content specific features, lexicon based classification, sentiment classification, Senti word net.  ... 
doi:10.7763/ijmlc.2015.v5.525 fatcat:vbl3g5x35vbuncsj6qtsyqoehi
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