Offensive Language Identification in Greek

Zeses Pitenis, Marcos Zampieri, Tharindu Ranasinghe

    Research output: Chapter in Book/Published conference outputConference publication


    As offensive language has become a rising issue for online communities and social media platforms, researchers have been investigating ways of coping with abusive content and developing systems to detect its different types: cyberbullying, hate speech, aggression, etc. With a few notable exceptions, most research on this topic so far has dealt with English. This is mostly due to the availability of language resources for English. To address this shortcoming, this paper presents the first Greek annotated dataset for offensive language identification: the Offensive Greek Tweet Dataset (OGTD). OGTD is a manually annotated dataset containing 4,779 posts from Twitter annotated as offensive and not offensive. Along with a detailed description of the dataset, we evaluate several computational models trained and tested on this data.
    Original languageEnglish
    Title of host publicationProceedings of the 12th Language Resources and Evaluation Conference
    Publication statusPublished - May 2020


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