Browsing by Author "N, N."

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    Creation and Classification of Kannada Meme Dataset: Exploring Domain and Troll Categories
    (Springer Science and Business Media Deutschland GmbH, 2024) Kundargi, S.Y.; N, N.; Anand Kumar, M.; Chakravarthi, B.R.
    In this pioneering research, the first-ever Kannada memes dataset is established, marking a groundbreaking contribution. This dataset encompasses 2002 memes, spanning various categories such as movies, politics, sports, trolls, and non-troll memes. The classification models have been meticulously fine-tuned for memes, incorporating image-based models using DenseNet169 and text-based models with BERT for text encoding. An innovative multimodal approach combines insights from images and text, acknowledging the comprehensive nature of meme content. Throughout the study, model strengths and weaknesses are assessed, emphasizing their reliance on cutting-edge technologies like Deep Learning and Natural Language Processing. Valuable improvements are recommended, such as the implementation of oversampling techniques and regular dataset updates to enhance relevance and accuracy. This work extends beyond immediate research, contributing to the development of adaptive meme classification systems, particularly for Kannada-speaking audiences within the evolving meme culture landscape. Notably, the results indicate that multimodal models achieved the best scores for domain classification, while image-based models excelled in troll meme classification, further highlighting the significance of this approach within the field. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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    Telugu Meme Dataset and Baseline System for Automatic Identification of Domain, and Troll in Memes
    (Springer Science and Business Media Deutschland GmbH, 2024) N, N.; Adnan Raqeeb, S.; Sai Manoj Reddy, P.; Sunil Kumar, C.V.; Anand Kumar, M.; Chakravarthi, B.R.
    Everyone 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.