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Analyzing memes on the internet has emerged as a crucial endeavor due to theimpact 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. Inthis paper, we present the overview of the Memotion 3 shared task, as part ofthe DeFactify 2 workshop at AAAI-23. The task released an annotated dataset ofHindi-English code-mixed memes based on their Sentiment (Task A), Emotion (TaskB), and Emotion intensity (Task C). Each of these is defined as an individualtask and the participants are ranked separately for each task. Over 50 teamsregistered for the shared task and 5 made final submissions to the test set ofthe Memotion 3 dataset. CLIP, BERT modifications, ViT etc. were the mostpopular models among the participants along with approaches such asStudent-Teacher model, Fusion, and Ensembling. The best final F1 score for TaskA is 34.41, Task B is 79.77 and Task C is 59.82.

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