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        <title>MemoSYS at SemEval-2020 Task 8: Multimodal Emotion Analysis in Memes</title>
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    <name type="personal">
        <namePart type="given">Irina</namePart>
        <namePart type="family">Bejan</namePart>
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            <title>Proceedings of the Fourteenth Workshop on Semantic Evaluation</title>
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        <name type="personal">
            <namePart type="given">Aurelie</namePart>
            <namePart type="family">Herbelot</namePart>
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        <name type="personal">
            <namePart type="given">Xiaodan</namePart>
            <namePart type="family">Zhu</namePart>
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        <name type="personal">
            <namePart type="given">Alexis</namePart>
            <namePart type="family">Palmer</namePart>
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        <name type="personal">
            <namePart type="given">Nathan</namePart>
            <namePart type="family">Schneider</namePart>
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        <name type="personal">
            <namePart type="given">Jonathan</namePart>
            <namePart type="family">May</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Shutova</namePart>
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            <publisher>International Committee for Computational Linguistics</publisher>
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    <abstract>Internet memes are one of the most viral types of content in social media and are equally used in promoting hate speech. Towards a more broad understanding of memes, this paper describes the MemoSys system submitted in Task 8 of SemEval 2020, which aims to classify the sentiment of Internet memes and provide a minimum description of the type of humor it depicts (sarcastic, humorous, offensive, motivational) and its semantic scale. The solution presented covers four deep model architectures which are based on a joint fusion between the VGG16 pre-trained model for extracting visual information and the canonical BERT model or TF-IDF for text understanding. The system placed 5th of 36 participating systems in the task A, offering promising prospects to the use of transfer learning to approach Internet memes understanding.</abstract>
    <identifier type="citekey">bejan-2020-memosys</identifier>
    <identifier type="doi">10.18653/v1/2020.semeval-1.155</identifier>
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        <url>https://aclanthology.org/2020.semeval-1.155</url>
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        <date>2020-12</date>
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            <start>1172</start>
            <end>1178</end>
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%0 Conference Proceedings
%T MemoSYS at SemEval-2020 Task 8: Multimodal Emotion Analysis in Memes
%A Bejan, Irina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F bejan-2020-memosys
%X Internet memes are one of the most viral types of content in social media and are equally used in promoting hate speech. Towards a more broad understanding of memes, this paper describes the MemoSys system submitted in Task 8 of SemEval 2020, which aims to classify the sentiment of Internet memes and provide a minimum description of the type of humor it depicts (sarcastic, humorous, offensive, motivational) and its semantic scale. The solution presented covers four deep model architectures which are based on a joint fusion between the VGG16 pre-trained model for extracting visual information and the canonical BERT model or TF-IDF for text understanding. The system placed 5th of 36 participating systems in the task A, offering promising prospects to the use of transfer learning to approach Internet memes understanding.
%R 10.18653/v1/2020.semeval-1.155
%U https://aclanthology.org/2020.semeval-1.155
%U https://doi.org/10.18653/v1/2020.semeval-1.155
%P 1172-1178

Markdown (Informal)

[MemoSYS at SemEval-2020 Task 8: Multimodal Emotion Analysis in Memes](https://aclanthology.org/2020.semeval-1.155) (Bejan, SemEval 2020)

• MemoSYS at SemEval-2020 Task 8: Multimodal Emotion Analysis in Memes (Bejan, SemEval 2020)

ACL

• Irina Bejan. 2020. MemoSYS at SemEval-2020 Task 8: Multimodal Emotion Analysis in Memes. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1172–1178, Barcelona (online). International Committee for Computational Linguistics.