Essays about: "hate tweets"
Found 5 essays containing the words hate tweets.
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1. A Hybrid Approach to Hate Speech Detection
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : An interesting question is to what extent can background knowledge help in the context of text classification. To address this in more detail, can a traditional rulebased classifier help boost the accuracy of learned models? We explore this here for detecting hate speech and offensive language in online text. READ MORE
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2. #Laïcité on Twitter : A Critical Discourse Analysis of Hashtag #Laïcité and Its Use in Discourses on Islam in the French Republic
University essay from Malmö universitet/Institutionen för konst, kultur och kommunikation (K3)Abstract : This thesis explores the Twitter discourse surrounding French secularism, referred to as laïcité, and its interplay with Islam in France. The research aims to provide an in-depth synchronic analysis of patterns and Twitter users’ language and rhetoric when discussing the principle. READ MORE
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3. Classifying Hate Speech using Fine-tuned Language Models
University essay from Uppsala universitet/Statistiska institutionenAbstract : Given the explosion in the size of social media, the amount of hate speech is also growing. To efficiently combat this issue we need reliable and scalable machine learning models. Current solutions rely on crowdsourced datasets that are limited in size, or using training data from self-identified hateful communities, that lacks specificity. READ MORE
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4. Detecting hate speech on Twitter
University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)Abstract : Hate speech and cyberbullying on social media platform Twitter is a grow-ing issue, and to combat this they turn to machine learning and computerscience. This study will investigate and compare different configurationsfor the naive Bayes classifier when classifying hate speech on Twitter. READ MORE
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5. Classification of Hate Tweets and Their Reasons using SVM
University essay from Uppsala universitet/Avdelningen för datalogiAbstract : Denna studie fokuserar på att klassificera hat-meddelanden riktade mot mobiloperatörerna Verizon, AT&T and Sprint. Huvudsyftet är att med hjälp av maskininlärningsalgoritmen Support Vector Machines (SVM) klassificera meddelanden i fyra kategorier - Hat, Orsak, Explicit och Övrigt - för att kunna identifiera ett hat-meddelande och dess orsak. READ MORE