A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
Filters
Simpler is better? Lexicon-based ensemble sentiment classification beats supervised methods
2014
2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)
Preserved Fulltext
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
2020
Journal of clean energy technologies
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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
2020
International Journal of Emerging Trends in Engineering Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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
2021
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
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
2015
Entropy
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
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]
2018
Artificial Intelligence - Emerging Trends and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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
2016
Indian Journal of Science and Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
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
2016
International Journal of Computer Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
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
2019
International Journal of Information Technology and Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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]
2016
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
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
2022
Healthcare
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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
2018
ACM Transactions on Management Information Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
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
2021
Turkish Journal of Computer and Mathematics Education
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
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
2018
Proceedings of The 12th International Workshop on Semantic Evaluation
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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
2015
International Journal of Machine Learning and Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
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
« Previous
Showing results 1 — 15 out of 771 results