Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Word association norms, mutual information, and lexicography
Computational Linguistics
Foundations of statistical natural language processing
Foundations of statistical natural language processing
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
News Sensitive Stock Trend Prediction
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
Using Semantic Dependencies to Mine Depressive Symptoms from Consultation Records
IEEE Intelligent Systems
Mining opinions from the Web: Beyond relevance retrieval
Journal of the American Society for Information Science and Technology
Affect Analysis of Web Forums and Blogs Using Correlation Ensembles
IEEE Transactions on Knowledge and Data Engineering
Using text mining and sentiment analysis for online forums hotspot detection and forecast
Decision Support Systems
G-ANMI: A mutual information based genetic clustering algorithm for categorical data
Knowledge-Based Systems
Annotation and verification of sense pools in OntoNotes
Information Processing and Management: an International Journal
Build Chinese emotion lexicons using a graph-based algorithm and multiple resources
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
An intraday market risk management approach based on textual analysis
Decision Support Systems
Word AdHoc Network: Using Google Core Distance to extract the most relevant information
Knowledge-Based Systems
Learning to rank with document ranks and scores
Knowledge-Based Systems
SentiFul: A Lexicon for Sentiment Analysis
IEEE Transactions on Affective Computing
A dynamic threshold decision system for stock trading signal detection
Applied Soft Computing
Journal of Biomedical Informatics
A text-based decision support system for financial sequence prediction
Decision Support Systems
Neural network method to predict stock price movement based on stock information entropy
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Data mining techniques for the screening of age-related macular degeneration
Knowledge-Based Systems
IEEE Transactions on Affective Computing
A Hybrid System Integrating a Wavelet and TSK Fuzzy Rules for Stock Price Forecasting
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
HAL-Based Evolutionary Inference for Pattern Induction From Psychiatry Web Resources
IEEE Transactions on Evolutionary Computation
Identifying the semantic orientation of terms using S-HAL for sentiment analysis
Knowledge-Based Systems
Mutual information based input feature selection for classification problems
Decision Support Systems
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Sentiment classification of stock market news involves identifying positive and negative news articles, and is an emerging technique for making stock trend predictions which can facilitate investor decision making. In this paper, we propose the presence and intensity of emotion words as features to classify the sentiment of stock market news articles. To identify such words and their intensity, a contextual entropy model is developed to expand a set of seed words generated from a small corpus of stock market news articles with sentiment annotation. The contextual entropy model measures the similarity between two words by comparing their contextual distributions using an entropy measure, allowing for the discovery of words similar to the seed words. Experimental results show that the proposed method can discover more useful emotion words and their corresponding intensity, thus improving classification performance. Performance was further improved by the incorporation of intensity into the classification, and the proposed method outperformed the previously-proposed pointwise mutual information (PMI)-based expansion methods.