Abstract
The paper describes results of research on applicability of a new tool called Distributed Machine Learning Toolkit (DMTK) to detect hate speech on the Internet. For this purpose, the Word Embedding module was used, which uses the word2vec method to create a vector representation of the word. These representations were used for vector recording of entries posted on twitter and then they were subjected to classification using LightGBM, a classifier using gradient boosting methods. As a reference, in order to compare results provided by DMTK, two free of charge machine learning algorithms Gensim and GloVe were scrutinized.
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Woda, M., Torbiarczyk, M. (2019). Use of Distributed Machine Learning Toolkit for Searching Content Promoting Hate Speech on the Web. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Contemporary Complex Systems and Their Dependability. DepCoS-RELCOMEX 2018. Advances in Intelligent Systems and Computing, vol 761. Springer, Cham. https://doi.org/10.1007/978-3-319-91446-6_50
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