文章基本信息

标题：IIIT_DWD@EACL2021: Identifying Troll Meme inTamil using a hybrid deep learning approach
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作者：Ankit Kumar Mishra ; Sunil Saumya
期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2021
卷号：2021
页码：243-248
语种：English
出版社：ACL Anthology
摘要：Social media are an open forum that allows people to share their knowledge, abilities, talents, ideas, or expressions. Simultaneously, it also allows people to post disrespectful, trolling, defamation, or negative content targeting users or the community based on their gender, race, religious beliefs, etc. Such posts are available in the form of text, image, video, and meme. Among them, memes are currently widely used to disseminate offensive material amongst people. It is primarily in the form of pictures and text. In the present paper, troll memes are identified, which is necessary to create a healthy society. To do so, a hybrid deep learning model combining convolutional neural networks and bidirectional long short term memory is proposed to identify trolled memes. The dataset used in the study is a part of the competition EACL 2021: Troll Meme classification in Tamil. The proposed model obtained 10th rank in the competition and reported a precision of 0.52, recall 0.59, and weighted F10.3.