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Comparative Study on Sentiment Analysis in Image-Based Memes

Publication Type : Conference Proceedings

Publisher : IEEE

Source : 2023 9th International Conference on Smart Computing and Communications (ICSCC)

Url : https://doi.org/10.1109/icscc59169.2023.10334945

Campus : Kochi

School : School of Computing

Year : 2023

Abstract : In this electronic age of computers and mobile devices, users frequently share and express their opinions through videos and images. Memes are shared as a means of expressing the user’s thoughts, feelings, experiences, and sentiments. Memes are being used extensively, which has both pros and cons. Alarmingly more offensive and sensitive memes are being shared, which may be upsetting to other people’s social and cultural values. In order to classify these memes as positive or negative, this study will investigate their meaning. Thus, it will allow us to comprehend the user’s opinions on many topics and concepts. We have deployed different multimodal and unimodal on Facebook’s dataset of hateful memes and categorized the memes into positive and negative types. The best modal found was BERT, which outperformed all other algorithms with an accuracy of 93%.

Cite this Research Publication : G Niranjana, P Vyshnavi, K R Sreelakshmi, G Deepa, Comparative Study on Sentiment Analysis in Image-Based Memes, 2023 9th International Conference on Smart Computing and Communications (ICSCC), IEEE, 2023, https://doi.org/10.1109/icscc59169.2023.10334945

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