Telugu Meme Dataset and Baseline System for Automatic Identification of Domain, and Troll in Memes

dc.contributor.authorN, N.
dc.contributor.authorAdnan Raqeeb, S.
dc.contributor.authorSai Manoj Reddy, P.
dc.contributor.authorSunil Kumar, C.V.
dc.contributor.authorAnand Kumar, M.
dc.contributor.authorChakravarthi, B.R.
dc.date.accessioned2026-02-06T06:34:07Z
dc.date.issued2024
dc.description.abstractEveryone now uses social media to communicate information and ideas, which has become a requirement for everyone. Social media posts can offend people or be helpful or educational for them. Memes are one type of media that is disseminated in this way through direct messages, videos, or photographs. A meme is an image or video that captures the opinions and sentiments of a particular group of people. Memes can be trolling or not, and they include an image and text that express an emotion. Most memes are unique to a particular linguistic group of people. The most frequent cause of this is different languages. Memes must be categorized since studying them can help us understand the interests of each user. As both are necessary for interpretation, the meme cannot be considered acceptable if we only gaze at the text or the image. In this article, we provided a method for categorizing memes in Telugu that considers both the meme’s text and visual features, classifies trolling and non-trolling memes, attempt to determine the emotion the meme conveys and categorizes the meme according to the domain it belongs to. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
dc.identifier.citationCommunications in Computer and Information Science, 2024, Vol.2046 CCIS, , p. 18-33
dc.identifier.issn18650929
dc.identifier.urihttps://doi.org/10.1007/978-3-031-58495-4_2
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/29067
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.titleTelugu Meme Dataset and Baseline System for Automatic Identification of Domain, and Troll in Memes

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