Publication

A dataset for troll classification of Tamil memes

Chakravarthi, Bharathi Raja
Varma, Pranav
Arcan, Mihael
McCrae, John P.
Buitelaar, Paul
Shardul, Suryawanshi
Citation
Chakravarthi, Bharathi Raja, Varma, Pranav, Arcan, Mihael, McCrae, John P., Buitelaar, Paul, & Shardul, Suryawanshi. (2020). A dataset for troll classification of Tamil memes. Paper presented at the Language Resources and Evaluation Conference (LREC 2020) 5th Workshop on Indian Language Data: Resources and Evaluation, Marseille, France, 11-16 May.
Abstract
Social media are interactive platforms that facilitate the creation or sharing of information, ideas or other forms of expression among people. This exchange is not free from offensive, trolling or malicious contents targeting users or communities. One way of trolling is by making memes, which in most cases combines an image with a concept or catchphrase. The challenge of dealing with memes is that they are region-specific and their meaning is often obscured in humour or sarcasm. To facilitate the computational modelling of trolling in the memes for Indian languages, we created a meme dataset for Tamil (TamilMemes). We annotated and released the dataset containing suspected trolls and not-troll memes. In this paper, we use the a image classification to address the difficulties involved in the classification of troll memes with the existing methods. We found that the identification of a troll meme with such an image classifier is not feasible which has been corroborated with precision, recall and F1-score.
Publisher
European Language Resources Association (ELRA)
Publisher DOI
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland