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This research deals with analyzing the hate speech with a novel method of combining LDA with SOM. Experimentally no of topics derived from the dataset after the application of LDA was 10. Dominant topic was calculated for each data value. This data was fed to a SOM network initially assigned with random weights. The learning rate for SOM was 0.5…

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yash-saini/Hate-Speech-Analysis

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Hate-Speech-Analysis-Using-Latent-Dirichlet-Allocation-&-Self-Organizing-Maps

This research deals with analyzing the hate speech with a novel method of combining LDA with SOM. Experimentally no of topics derived from the dataset after the application of LDA was 10. Dominant topic was calculated for each data value. This data was fed to a SOM network initially assigned with random weights. The learning rate for SOM was 0.5 and number of iterations were 100. The clusters were formed as a result and the map was displayed.

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This research deals with analyzing the hate speech with a novel method of combining LDA with SOM. Experimentally no of topics derived from the dataset after the application of LDA was 10. Dominant topic was calculated for each data value. This data was fed to a SOM network initially assigned with random weights. The learning rate for SOM was 0.5…

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