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Overview of Memotion 3: Sentiment and Emotion Analysis of Codemixed Hinglish Memes

2023-09-12 · Shreyash Mishra, S Suryavardan, Megha Chakraborty, Parth Patwa, Anku Rani, Aman Chadha, Aishwarya Reganti, Amitava Das, Amit Sheth, Manoj Chinnakotla, Asif Ekbal, Srijan Kumar

Analyzing memes on the internet has emerged as a crucial endeavor due to the impact this multi-modal form of content wields in shaping online discourse. Memes have become a powerful tool for expressing emotions and sentiments, possibly even spreading hate and misinformation, through humor and sarcasm. In this paper, we present the overview of the Memotion 3 shared task, as part of the DeFactify 2 workshop at AAAI-23. The task released an annotated dataset of Hindi-English code-mixed memes based on their Sentiment (Task A), Emotion (Task B), and Emotion intensity (Task C). Each of these is defined as an individual task and the participants are ranked separately for each task. Over 50 teams registered for the shared task and 5 made final submissions to the test set of the Memotion 3 dataset. CLIP, BERT modifications, ViT etc. were the most popular models among the participants along with approaches such as Student-Teacher model, Fusion, and Ensembling. The best final F1 score for Task A is 34.41, Task B is 79.77 and Task C is 59.82.

📄 PDF Abstract BibTeX arXiv:2309.06517

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Emotion Recognition Misinformation

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Multi-Head Attention 설명 없음

Attention 설명 없음

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

Attention Dropout Attention Dropout is a type of dropout used in attention-based architectures, where elements are randomly dropped out of the…

Residual Connection 설명 없음

Adam 설명 없음

Weight Decay 설명 없음

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Memotion 3: Dataset on Sentiment and Emotion Analysis of Codemixed Hindi-English Memes

2023-03-17 · Shreyash Mishra, S Suryavardan, Parth Patwa, Megha Chakraborty 외

Memes are the new-age conveyance mechanism for humor on social media sites. Memes often include an image and some text. Memes can be used to promote disinformation or hatred, thus it is crucial to investigate in details.…

Emotion Recognition

Urszula Wali\'nska at SemEval-2020 Task 8: Fusion of Text and Image Features Using LSTM and VGG16 for Memotion Analysis

2020-12-01 · SEMEVAL 2020 · Urszula Wali{\'n}ska, J{\k{e}}drzej Potoniec

In this paper, we describe the entry to the task of Memotion Analysis. The sentiment analysis of memes task, is motivated by a pervasive problem of offensive content spread in social media, up to the present time. In fac…

Sentiment Analysis Sentiment Classification

BERT at SemEval-2020 Task 8: Using BERT to Analyse Meme Emotions

2020-12-01 · SEMEVAL 2020 · Adithya Avvaru, Sanath Vobilisetty

Sentiment analysis, being one of the most sought after research problems within Natural Language Processing (NLP) researchers. The range of problems being addressed by sentiment analysis is increasing. Till now, most of …

Sentiment Analysis

NUAA-QMUL at SemEval-2020 Task 8: Utilizing BERT and DenseNet for Internet Meme Emotion Analysis

2020-11-05 · SEMEVAL 2020 · XIAOYU GUO, Jing Ma, Arkaitz Zubiaga

This paper describes our contribution to SemEval 2020 Task 8: Memotion Analysis. Our system learns multi-modal embeddings from text and images in order to classify Internet memes by sentiment. Our model learns text embed…

Emotion Recognition image-classification Image Classification

NYCU-TWO at Memotion 3: Good Foundation, Good Teacher, then you have Good Meme Analysis

2023-02-13 · Yu-Chien Tang, Kuang-Da Wang, Ting-Yun Ou, Wen-Chih Peng

This paper presents a robust solution to the Memotion 3.0 Shared Task. The goal of this task is to classify the emotion and the corresponding intensity expressed by memes, which are usually in the form of images with sho…

Knowledge Distillation Sentiment Analysis