Analyzing the effectiveness and applicability of co-training
Proceedings of the ninth international conference on Information and knowledge management
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
A simple approach to building ensembles of Naive Bayesian classifiers for word sense disambiguation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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
The predictive power of online chatter
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
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
Using Online Conversations to Study Word-of-Mouth Communication
Marketing Science
ARSA: a sentiment-aware model for predicting sales performance using blogs
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Do online reviews matter? - An empirical investigation of panel data
Decision Support Systems
Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web
Management Science
Using text mining and sentiment analysis for online forums hotspot detection and forecast
Decision Support Systems
Movie reviews and revenues: an experiment in text regression
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Twitter based system: Using Twitter for disambiguating sentiment ambiguous adjectives
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
A Dynamic Model of the Effect of Online Communications on Firm Sales
Marketing Science
Deriving the Pricing Power of Product Features by Mining Consumer Reviews
Management Science
RETRACTED: Sentiment Analysis in Decision Sciences Research: An Illustration to IT Governance
Decision Support Systems
Social Media and Firm Equity Value
Information Systems Research
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This study aims to investigate the effect of social media and conventional media, their relative importance, and their interrelatedness on short term firm stock market performances. We use a novel and large-scale dataset that features daily media content across various conventional media and social media outlets for 824 public traded firms across 6 industries. Social media outlets include blogs, forums, and Twitter. Conventional media includes major newspapers, television broadcasting companies, and business magazines. We apply the advanced sentiment analysis technique that goes beyond the number of mentions (counts) to analyze the overall sentiment of each media resource toward a specific company on the daily basis. We use stock return and risk as the indicators of companies' short-term performances. Our findings suggest that overall social media has a stronger relationship with firm stock performance than conventional media while social and conventional media have a strong interaction effect on stock performance. More interestingly, we find that the impact of different types of social media varies significantly. Different types of social media also interrelate with conventional media to influence stock movement in various directions and degrees. Our study is among the first to examine the effect of multiple sources of social media along with the effect of conventional media and to investigate their relative importance and their interrelatedness. Our findings suggest the importance for firms to differentiate and leverage the unique impact of various sources of media outlets in implementing their social media marketing strategies.