Sökning: "hate speech detection"

Visar resultat 1 - 5 av 12 uppsatser innehållade orden hate speech detection.

  1. 1. IDENTIFYING HATE SPEECH IN SOCIAL MEDIA THROUGH CONTENT AND SOCIAL CONNECTIONS ANALYSIS

    Master-uppsats, Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteori

    Författare :Milan Stanišić; [2023-06-19]
    Nyckelord :hate speech; social media; natural language processing; classification;

    Sammanfattning : Hate speech is a problem which puts its targets at risk of serious harm. It spreads fast and has a real influence on the society because of the ubiquity of the internet and social media, and so various research efforts have been put to find solutions to automatic hate speech detection. LÄS MER

  3. 2. Mitigating Unintended Bias in Toxic Comment Detection using Entropy-based Attention Regularization

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

    Författare :Fabio Camerota; [2023]
    Nyckelord :XLNet; BERT; Toxic Comment Classification; Entropy-based Attention Regularization; XLNet; BERT; Toxisk Kommentar Klassificering; Entropibaserad uppmärksamhetsreglering;

    Sammanfattning : The proliferation of hate speech is a growing challenge for social media platforms, as toxic online comments can have dangerous consequences also in real life. There is a need for tools that can automatically and reliably detect hateful comments, and deep learning models have proven effective in solving this issue. LÄS MER

  4. 3. Towards End-User Understanding: Exploring Explanations For Profanity Detection

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Noah Öberg; [2023]
    Nyckelord :;

    Sammanfattning : Current text classification models can accurately identify instances of specific categories, such as hate speech or bad language, but they often don’t provide clear explanations to the end user for their decisions. This can lead to confusion or mistrust in the results, especially in sensitive applications where the consequences of misclassification can be significant. LÄS MER

  5. 4. 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

  7. 5. Can Hatescan Detect Antisemitic Hate Speech

    Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Olle Nyrén; [2023]
    Nyckelord :Artificial intelligence; hate speech detection; hate speech; antisemitism;

    Sammanfattning : This thesis focuses on how well Hatescan, a hate speech detector built on the same Natural Language Processing and AI algorithms used in most online hate speech detectors, can detect different categories of antisemitism as well as whether or not it is worse at detecting implicit antisemitism than explicit antisemitism. The ability of hate speech detectors to detect antisemitic hate speech is a pressing issue. LÄS MER