Conduct a study on the relation between conversation structure and toxicity
- Does selecting by toxicity successfully select conversations gone bad?
- How much does context matter when people evaluate the toxicity of a comment?
- Topic (page & time)
- Conversation length & timing
- Previous comments
- How good are human annotators at predicting if a conversation will go bad?
- Can we train a model to help with this task directly?
Collaborators
- Nithum Thain
- Lucas Dixon
- Yiqing Hua
- Cristian Danescu-Niculescu-Mizil
In Q2 we aim to:
- finalize the labeling schema
- generate human labels for comments and conversations and analyze them
- train a model to answer the above questions
- submit a paper (moving the release of assets from this research to a separate task: human/machine labeled data, code, on-wiki report, preprint)
If the paper is accepted (acceptance notification is in December), we're planning to write a story on the Wikimedia Blog (and potentially the Jigsaw blog), referencing the above assets.