Memotion Dataset

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Memotion Dataset

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Memotion Dataset

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Memotion Dataset

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Memotion Dataset

Description

Explore the Memotion Dataset, a groundbreaking collection of 8K annotated memes designed for advanced sentiment and humor classification. Ideal for researchers focusing on automated meme analysis.

Description:

Social media content comprises various modalities, including text, images, and audio. While the NLP and Computer Vision communities often analyze these modalities separately, the unique nature of Internet memes demands a hybrid approach for effective computational processing. Memes are increasingly prevalent on platforms like Facebook, Instagram, and Twitter, and their multimodal content necessitates comprehensive analysis. Despite their ubiquity, there is limited research focused on meme emotion analysis. This proposal aims to spotlight the automatic processing of Internet memes within the research community. The Memotion analysis task introduces 8K annotated memes, tagged with human-annotated sentiments and types of humor, such as sarcasm, humor, or offensiveness.

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Multimodal Social Media

In recent years, the widespread presence of Internet memes on social media has garnered significant interest. Memes, among the most frequently typed English words (Sonnad, 2018), often stem from shared social and cultural experiences, like TV shows or popular characters (e.g., the “One Does Not Simply” meme from “The Lord of the Rings”). Memes are deeply embedded in Internet culture, reflecting community opinions and social discourse (Gal et al., 2016). However, the rise of online hate speech has compounded the challenge of moderating offensive content. The addition of memes, which combine visual cues and language, complicates detection efforts. Current moderation strategies rely heavily on human intervention, but the volume of multimodal content is rapidly becoming unmanageable. Thus, there’s a pressing need for automated multimodal social media analysis.

The Memotion Analysis Task

Task A: Sentiment Classification: Classify a given meme as positive, negative, or neutral.
Task B: Humor Classification: Identify the type of humor in a meme, categorizing it as sarcastic, humorous, offensive, or other. A meme can belong to more than one category.
Task C: Scales of Semantic Classes: Quantify the extent to which a particular effect (e.g., sarcasm, humor, offensiveness) is expressed in the meme. Detailed quantifications are provided in the dataset.

Evaluation Criteria

Task A: Evaluated using macro F1 score.
Tasks B and C: Evaluated using macro F1 score for each subtask, with an overall average score reported.