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Machine learning-based automated tool to detect Sinhala hate speech in images

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dc.contributor.author Silva, E
dc.contributor.author Nandathilaka, M
dc.contributor.author Dalugoda, S
dc.contributor.author Amarasinghe, T
dc.contributor.author Ahangama, S
dc.contributor.author Weerasuriya, GT
dc.contributor.editor Ganegoda, GU
dc.contributor.editor Mahadewa, KT
dc.date.accessioned 2022-11-10T04:40:50Z
dc.date.available 2022-11-10T04:40:50Z
dc.date.issued 2021-12
dc.identifier.citation E. Silva, M. Nandathilaka, S. Dalugoda, T. Amarasinghe, S. Ahangama and G. T. Weerasuriya, "Machine Learning-Based Automated Tool to Detect Sinhala Hate Speech in Images," 2021 6th International Conference on Information Technology Research (ICITR), 2021, pp. 1-7, doi: 10.1109/ICITR54349.2021.9657453. en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/19466
dc.description.abstract Social media platforms have emerged rapidly with technological advancements. Facebook, the most widely used social media platform has been the primary reason for the spread of hatred in Sri Lanka in the recent past. When a post with Sinhala hate content is reported on Facebook, it is translated to the English language before the review of the moderators. In most instances, the translated content has a different context compared to the original post. This results in concluding that the reported post does not violate the established policies and guidelines concerning hate content. Hence, an effective approach needs to be in place to address the aforementioned problem. This research project proposes a solution through an automated tool that is capable of detecting hate content presented in Sinhala phrases extracted from Facebook posts/memes. The tool accepts an image that contains Sinhala texts, extracts the text using a Convolutional Neural Network (CNN) model, preprocesses the text using Natural Language Processing (NLP) techniques, analyzes the preprocessed text to identify hate intensity level and finally classifies the text into four main domains named Political, Race, Religion and Gender using a text classification model. en_US
dc.language.iso en en_US
dc.publisher Faculty of Information Technology, University of Moratuwa. en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9657453 en_US
dc.subject Hate content en_US
dc.subject Facebook en_US
dc.subject Sinhala language en_US
dc.subject Convolutional neural network en_US
dc.subject Natural language processing en_US
dc.subject Text classifier model en_US
dc.title Machine learning-based automated tool to detect Sinhala hate speech in images en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty IT en_US
dc.identifier.department Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa. en_US
dc.identifier.year 2021 en_US
dc.identifier.conference 6th International Conference in Information Technology Research 2021 en_US
dc.identifier.place Moratuwa, Sri Lanka en_US
dc.identifier.proceeding Proceedings of the 6th International Conference in Information Technology Research 2021 en_US
dc.identifier.doi doi: 10.1109/ICITR54349.2021.9657453 en_US


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  • ICITR - 2021 [39]
    International Conference on Information Technology Research (ICITR)

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