Thesis Details
Automatizovaná detekce ofenzivního jazyka a nenávistných projevů v přirozeném jazyce
This thesis discusses hate speech and offensive language phenomenon, their respective definitions and their occurrence in natural language. It describes previously used methods of solving the detection. An evaluation of available data sets suitable for the problem of detection is provided. The thesis aims to provide additional methods of solving the detection of this issue and it compares the results of these methods. Five models were selected in total. Two of them are focused on feature extraction and the remaining three are neural network models. I have experimentally evaluated the success of the implemented models. The results of this thesis allow for comparison of the typical approaches with the methods leveraging the newest findings in terms of machine learning that are used for the classification of hate speech and offensive language.
natural language processing, offensive language, hate speech, classification, machine learning, detection, text processing
Hliněná Dana, doc. RNDr., Ph.D. (DMAT FEEC BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Orság Filip, Ing., Ph.D. (DITS FIT BUT), člen
Rychlý Marek, RNDr., Ph.D. (DIFS FIT BUT), člen
@bachelorsthesis{FITBT21454, author = "Al\v{z}beta \v{S}tajerov\'{a}", type = "Bachelor's thesis", title = "Automatizovan\'{a} detekce ofenzivn\'{i}ho jazyka a nen\'{a}vistn\'{y}ch projev\r{u} v p\v{r}irozen\'{e}m jazyce", school = "Brno University of Technology, Faculty of Information Technology", year = 2019, location = "Brno, CZ", language = "czech", url = "https://www.fit.vut.cz/study/thesis/21454/" }