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- W4287704237 abstract "Memes have become an ubiquitous social media entity and the processing and analysis of suchmultimodal data is currently an active area of research. This paper presents our work on theMemotion Analysis shared task of SemEval 2020, which involves the sentiment and humoranalysis of memes. We propose a system which uses different bimodal fusion techniques toleverage the inter-modal dependency for sentiment and humor classification tasks. Out of all ourexperiments, the best system improved the baseline with macro F1 scores of 0.357 on SentimentClassification (Task A), 0.510 on Humor Classification (Task B) and 0.312 on Scales of SemanticClasses (Task C)." @default.
- W4287704237 created "2022-07-26" @default.
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- W4287704237 date "2020-07-28" @default.
- W4287704237 modified "2023-09-26" @default.
- W4287704237 title "DSC IIT-ISM at SemEval-2020 Task 8: Bi-Fusion Techniques for Deep Meme Emotion Analysis" @default.
- W4287704237 doi "https://doi.org/10.48550/arxiv.2008.00825" @default.
- W4287704237 hasPublicationYear "2020" @default.
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