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arXiv 2010.04470cs.CV

gundapusunil at SemEval-2020 Task 8: Multimodal Memotion Analysis

Language Technologies Research Centre(语言技术研究中心);KCIS, IIIT Hyderabad(海得拉巴国际信息技术研究所知识与数据工程中心)

Sunil Gundapu, Radhika Mamidi

英文摘要:

Recent technological advancements in the Internet and Social media usage have resulted in the evolution of faster and efficient platforms of communication. These platforms include visual, textual and speech mediums and have brought a unique social phenomenon called Internet memes. Internet memes are in the form of images with witty, catchy, or sarcastic text descriptions. In this paper, we present a multi-modal sentiment analysis system using deep neural networks combining Computer Vision and Natural Language Processing. Our aim is different than the normal sentiment analysis goal of predicting whether a text expresses positive or negative sentiment; instead, we aim to classify the Internet meme as a positive, negative, or neutral, identify the type of humor expressed and quantify the extent to which a particular effect is being expressed. Our system has been developed using CNN and LSTM and outperformed the baseline score.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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