The nature of statistical learning theory
The nature of statistical learning theory
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Mining product reputations on the Web
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
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
The sentimental factor: improving review classification via human-provided information
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Proceedings of the 11th international conference on Artificial intelligence and law
Scaling high-order character language models to gigabytes
Software '05 Proceedings of the Workshop on Software
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Assigning polarity scores to reviews using machine learning techniques
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Accessing Positive and Negative Online Opinions
UAHCI '09 Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services
A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
Sentiment classification of online Cantonese reviews by supervised machine learning approaches
International Journal of Web Engineering and Technology
Sentiment classification of Chinese traveler reviews by support vector machine algorithm
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Automatic web page annotation with google rich snippets
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems: Part II
Sentiment classification of Internet restaurant reviews written in Cantonese
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Music review classification enhanced by semantic information
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
An improved K-nearest-neighbor algorithm for text categorization
Expert Systems with Applications: An International Journal
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
Robust sense-based sentiment classification
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews
Expert Systems with Applications: An International Journal
Harnessing WordNet senses for supervised sentiment classification
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
An approach of semi-automatic public sentiment analysis for opinion and district
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
Electronic Commerce Research and Applications
Document-level sentiment classification: An empirical comparison between SVM and ANN
Expert Systems with Applications: An International Journal
Sample cutting method for imbalanced text sentiment classification based on BRC
Knowledge-Based Systems
A comparative study of feature selection and machine learning techniques for sentiment analysis
Proceedings of the 2012 ACM Research in Applied Computation Symposium
International Journal of Web Engineering and Technology
The decomposed k-nearest neighbor algorithm for imbalanced text classification
FGIT'12 Proceedings of the 4th international conference on Future Generation Information Technology
A reverse engineering approach for automatic annotation of Web pages
Multimedia Tools and Applications
Sentiment analysis of Hollywood movies on Twitter
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
A boosted SVM based sentiment analysis approach for online opinionated text
Proceedings of the 2013 Research in Adaptive and Convergent Systems
Text-based emotion classification using emotion cause extraction
Expert Systems with Applications: An International Journal
A boosted SVM based ensemble classifier for sentiment analysis of online reviews
ACM SIGAPP Applied Computing Review
| Hi-index | 12.06 |
The rapid growth in Internet applications in tourism has lead to an enormous amount of personal reviews for travel-related information on the Web. These reviews can appear in different forms like BBS, blogs, Wiki or forum websites. More importantly, the information in these reviews is valuable to both travelers and practitioners for various understanding and planning processes. An intrinsic problem of the overwhelming information on the Internet, however, is information overloading as users are simply unable to read all the available information. Query functions in search engines like Yahoo and Google can help users find some of the reviews that they needed about specific destinations. The returned pages from these search engines are still beyond the visual capacity of humans. In this research, sentiment classification techniques were incorporated into the domain of mining reviews from travel blogs. Specifically, we compared three supervised machine learning algorithms of Naive Bayes, SVM and the character based N-gram model for sentiment classification of the reviews on travel blogs for seven popular travel destinations in the US and Europe. Empirical findings indicated that the SVM and N-gram approaches outperformed the Naive Bayes approach, and that when training datasets had a large number of reviews, all three approaches reached accuracies of at least 80%.