Feature selection in SVM text categorization
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Optimal control by least squares support vector machines
Neural Networks
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Text Mining: Predictive Methods for Analyzing Unstructured Information
Text Mining: Predictive Methods for Analyzing Unstructured Information
Using appraisal groups for sentiment analysis
Proceedings of the 14th ACM international conference on Information and knowledge management
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Experimental perspectives on learning from imbalanced data
Proceedings of the 24th international conference on Machine learning
Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums
ACM Transactions on Information Systems (TOIS)
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Expert Systems with Applications: An International Journal
A survey on sentiment detection of reviews
Expert Systems with Applications: An International Journal
Feature subsumption for opinion analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Joint sentiment/topic model for sentiment analysis
Proceedings of the 18th ACM conference on Information and knowledge management
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
A framework of feature selection methods for text categorization
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Does SVM really scale up to large bag of words feature spaces?
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
Avoiding local minima in feedforward neural networks by simultaneous learning
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Fundamentals of Predictive Text Mining
Fundamentals of Predictive Text Mining
A Lexicon-Enhanced Method for Sentiment Classification: An Experiment on Online Product Reviews
IEEE Intelligent Systems
A study of information retrieval weighting schemes for sentiment analysis
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Unsupervised Artificial Neural Nets for Modeling Movie Sentiment
CICSYN '10 Proceedings of the 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks
Ensemble of feature sets and classification algorithms for sentiment classification
Information Sciences: an International Journal
Predicting consumer sentiments from online text
Decision Support Systems
Selecting Attributes for Sentiment Classification Using Feature Relation Networks
IEEE Transactions on Knowledge and Data Engineering
Exploring the use of word relation features for sentiment classification
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Automatically extracting polarity-bearing topics for cross-domain sentiment classification
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Sentiment analysis of customer reviews: balanced versus unbalanced datasets
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Sentiment classification based on supervised latent n-gram analysis
Proceedings of the 20th ACM international conference on Information and knowledge management
Imbalanced sentiment classification
Proceedings of the 20th ACM international conference on Information and knowledge management
Imbalanced Sentiment Classification with Multi-strategy Ensemble Learning
IALP '11 Proceedings of the 2011 International Conference on Asian Language Processing
Survey on mining subjective data on the web
Data Mining and Knowledge Discovery
Semi-supervised learning for imbalanced sentiment classification
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Comparing Support Vector Machines and Feedforward Neural Networks With Similar Hidden-Layer Weights
IEEE Transactions on Neural Networks
Augmenting weak semantic cognitive maps with an "abstractness" dimension
Computational Intelligence and Neuroscience - Special issue on Neurocognitive Models of Sense Making
Hi-index | 12.05 |
Document-level sentiment classification aims to automate the task of classifying a textual review, which is given on a single topic, as expressing a positive or negative sentiment. In general, supervised methods consist of two stages: (i) extraction/selection of informative features and (ii) classification of reviews by using learning models like Support Vector Machines (SVM) and Nai@?ve Bayes (NB). SVM have been extensively and successfully used as a sentiment learning approach while Artificial Neural Networks (ANN) have rarely been considered in comparative studies in the sentiment analysis literature. This paper presents an empirical comparison between SVM and ANN regarding document-level sentiment analysis. We discuss requirements, resulting models and contexts in which both approaches achieve better levels of classification accuracy. We adopt a standard evaluation context with popular supervised methods for feature selection and weighting in a traditional bag-of-words model. Except for some unbalanced data contexts, our experiments indicated that ANN produce superior or at least comparable results to SVM's. Specially on the benchmark dataset of Movies reviews, ANN outperformed SVM by a statistically significant difference, even on the context of unbalanced data. Our results have also confirmed some potential limitations of both models, which have been rarely discussed in the sentiment classification literature, like the computational cost of SVM at the running time and ANN at the training time.