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Cyberbullying Blocker Test Application for Android Devices
Abstract
In this chapter, the authors present an application for Android smartphones to automatically detect possible harmful content in input text. The developed application is aimed to test in practice the performance of the developed cyberbullying detection methods described in previous chapters. The final goal of the developed application will be to help mitigate the problem of cyberbullying by quickly detecting possibly harmful contents in user's entry and warning the user of the possible negative influence. The test application was prepared to use one of two methods for detection of harmful messages: a method inspired by a brute force search algorithm applied to language modelling and a method which uses seed words from three categories to calculate semantic orientation score SO-PMI-IR and then maximize the relevance of categories to specify harmfulness of a message (both methods were described in previous chapters). First tests showed that both methods are working properly under the Android environment.
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