Enterprise agility and the enabling role of information technology
European Journal of Information Systems - Including a special section on business agility and diffusion of information technology
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Bits of Personality Everywhere: Implicit User-Generated Content in the Age of Ambient Media
ISPA '08 Proceedings of the 2008 IEEE International Symposium on Parallel and Distributed Processing with Applications
Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web
Management Science
Location-based crowdsourcing: extending crowdsourcing to the real world
Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries
Twitter use by the U.S. Congress
Journal of the American Society for Information Science and Technology
Journal of Management Information Systems
Journal of Management Information Systems
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The business agility concept reflects an organization's need to develop sensing capabilities for being able to respond to changes in the business environment. Therefore, intelligent information systems are needed to support decision makers with accurate and timely information. Since corporate reputation is among the most valuable assets, organizations need efficient measuring techniques to manage it. Recently, due to the advent of social media new reputational challenges have emerged for firms, since such technologies significantly increase the risk for being associated with negative issues. Therefore, organizations should utilize there IT-systems for actively sensing social media content as a basis for a quick response to reputational threats. Accordingly, the authors provide an empirical example on how firms might improve reputation management through sensing social media. Specifically, the authors analyze a dataset of 271,207 messages about an American Bank collected on Twitter. For their empirical investigation, the applied automated sentiment analysis and manual content analysis.