Content Moderation
Example Inputs
Example
Outputs
Emotional Metaphors
Criteria: Does this text express emotions using metaphorical language?
Summary: Women are objectified, lack control, and are seen as tribal and revenge-minded. Feminism is criticized as promoting hostility and entitlement.
Gender Stereotype Metaphors
Criteria: Identify if metaphorical language reinforces gender stereotypes.
Summary: Gender stereotype metaphors perpetuate harmful beliefs about women's appearance, behavior, and worth, reinforcing societal biases and inequalities.
Patriarchy Metaphor
Criteria: Is metaphorical language used to discuss patriarchy?
Summary: The examples highlight the negative impact of patriarchy, objectification of women, gender discrimination, and societal expectations on women.
Metaphorical Personification
Criteria: Does this text use personification as a form of metaphorical language?
Summary: Using metaphorical personification, we depict women as tribal, men as evil, and society as oppressive.
Analysis
➡️ Try out analyzing this data with LLooM on this Colab notebook.
Task: Develop moderation policies for toxic content
Online content moderation has been a longstanding problem, and social media platforms devote significant resources to perform algorithmic content moderation. However, content moderation models are widely criticized for their errors and can often fail for marginalized communities. Given the substantial disagreement among the population on what constitutes toxic content, how can we instead design models that account for the unique moderation needs of individual communities? LLooM can help us monitor emergent patterns of harm in online communities, allowing us to identify and mitigate gaps in content moderation models.
Dataset: Toxic social media posts
We use a dataset of social media posts (from Twitter, Reddit, and 4chan) that gathers a diverse set of annotators’ perspectives on content toxicity with ratings from 17,280 U.S. survey participants on over 100,000 examples. We further filtered to a set of posts related to feminism as an example of a controversial topic area with a variety of user perspectives.