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Web Mining-Based Method for Cyberbullying Detection
Abstract
In this chapter, the authors present a method for automatic detection of cyberbullying entries based on a Web mining technique, in particular, on an extended SO-PMI-IR method calculating relevance of new input documents with training documents. The method uses seed words from three categories to calculate semantic orientation score and then maximizes the relevance of categories. The method outperformed previously proposed Web-mining-based methods in both laboratory and real-world conditions. The developed system is deployed and tested in practice. After a year of testing, the authors notice an over 30% point drop in its performance. They hypothesize on the reasons for the drop. To regain the lost performance and sustain it in the future, the authors propose additional improvements including automatic acquisition and filtering of seed words. Experimentally selected optimal improvements regained much of the lost performance.
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