Sökning: "offensive speech detection"

Hittade 5 uppsatser innehållade orden offensive speech detection.

  1. 1. A Hybrid Approach to Hate Speech Detection

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Simon Rickardsson; [2023]
    Nyckelord :;

    Sammanfattning : 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. LÄS MER

  3. 2. Multi-Label Toxic Comment Classification Using Machine Learning: An In-Depth Study

    Master-uppsats, Lunds universitet/Institutionen för datavetenskap

    Författare :Matilda Froste; Mosa Hosseini; [2023]
    Nyckelord :natural language processing; machine learning; offensive speech detection; transformers; multi-label classification; Technology and Engineering;

    Sammanfattning : The classification of toxic comments is a well-researched area with many techniques available. However, effectively managing multi-label categorization still requires a considerable amount of work. LÄS MER

  4. 3. Evaluating the robustness of DistilBERT to data shift in toxicity detection

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Caroline Larsen; [2022]
    Nyckelord :Machine learning; Natural Language Processing; DistilBERT; Toxicity Detection; Profanity Detection; Hate Speech Identification; Text preprocessing; Maskininlärning; naturligtspråkbehandling; DistilBERT; identifiering av kränkande språk; identifiering av svordomar; textbehandling;

    Sammanfattning : With the rise of social media, cyberbullying and online spread of hate have become serious problems with devastating consequences. Mentimeter is an interactive presentation tool enabling the presentation audience to participate by typing their own answers to questions asked by the presenter. LÄS MER

  5. 4. Transfer Learning for Multilingual Offensive Language Detection with BERT

    Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

    Författare :Camilla Casula; [2020]
    Nyckelord :;

    Sammanfattning : The popularity of social media platforms has led to an increase in user-generated content being posted on the Internet. Users, masked behind what they perceive as anonymity, can express offensive and hateful thoughts on these platforms, creating a need to detect and filter abusive content. LÄS MER

  7. 5. Multilingual identification of offensive content in social media

    Master-uppsats, Linköpings universitet/Artificiell intelligens och integrerade datorsystem

    Författare :Marc Pàmies Massip; [2020]
    Nyckelord :offensive language; hate speech; twitter; social media; nlp; ai; natural language processing; artificial intelligence; machine learning; bert; text classification;

    Sammanfattning : In today’s society there is a large number of social media users that are free to express their opinion on shared platforms. The socio-cultural differences between the people behind those accounts (in terms of ethnicity, gender, sexual orientation, religion, politics, . . . LÄS MER