Welcome to the website of EXIST 2025, the fifth edition of the sEXism Identification in Social neTworks task at CLEF 2025.

EXIST is a series of scientific events and shared tasks on sexism identification in social networks. EXIST aims to capture sexism in a broad sense, from explicit misogyny to other subtle expressions that involve implicit sexist behaviours (EXIST 2021, EXIST 2022, EXIST 2023, EXIST 2024). The fifth edition of the EXIST shared task will be held as a Lab in CLEF 2025, on September 9-12, 2025, in the UNED, Madrid, Spain.

Social Networks are the main platforms for social complaint, activism, etc. Movements like #MeTwoo, #8M or #Time’sUp have spread rapidly. Under the umbrella of social networks, many women all around the world have reported abuses, discriminations and other sexist experiences suffered in real life. Social networks are also contributing to the transmission of sexism and other disrespectful and hateful behaviours. In this context, automatic tools not only may help to detect and alert against sexism behaviours and discourses, but also to estimate how often sexist and abusive situations are found in social media platforms, what forms of sexism are more frequent and how sexism is expressed in these media. This Lab will contribute to developing applications to detect sexism.

In 2024 the EXIST campaing included multimedia content in the format of memes, steping forward research on more robust techniques to identify sexism in social networks. Following this line, this year we will focus TikTok videos in the challenge including in the dataset the three more important sources of sexism spreading: text, images and videos. Sexism on TikTok is also a growing concern as the platform’s algorithm often amplifies content that perpetuates gender stereotypes and internalized misogyny. Consequently, it is essential to develop automated multimodal tools capable of detecting sexism in text, images, and videos, to raise alarms or automatically remove such content from social networks. This lab will contribute to the creation of applications that identify sexist content in social media across all three formats.

While the three previous editions focused solely on detecting and classifying sexist textual messages, this new edition incorporates new tasks that center around images, particularly memes. Memes are images, typically humorous in nature, that are spread rapidly by social networks and Internet users. With this addition, we aim to encompass a broader spectrum of sexist manifestations in social networks, especially those disguised as humor. Consequently, it becomes imperative to develop automated multimodal tools capable of detecting sexism in both text and memes.

Similar to the approach in the 2023 and 2024 edition, this edition will also embrace the Learning With Disagreement (LeWiDi) paradigm for both the development of the dataset and the evaluation of the systems. The LeWiDi paradigm doesn’t rely on a single “correct” label for each example. Instead, the model is trained to handle and learn from conflicting or diverse annotations. This enables the system to consider various annotators’ perspectives, biases, or interpretations, resulting in a fairer learning process.

In previous editions, 223 teams from more than 50 countries submitted their results achieving impressive results, especially in the sexism detection task. However, there is still room for improvement, especially in when the problem is addressed under the LeWeDi paradigm in a multimedia context.

To be announced!

To be announced!