We lifted 4 functions out of this paper's own repositories and ran 4 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| LucilleN/dv-classifier | pwc_unofficial | 4 of 4 |
| Function | Status | Where it lives |
|---|---|---|
| build_vocab | Ran | LucilleN/dv-classifier/utils.py code served (permissive licence) · get_code("f699c30e20a82f96") |
| load_data | Ran | LucilleN/dv-classifier/data_loader.py code served (permissive licence) · get_code("c162df535f03de85") |
| reorder_minibatch | Ran | LucilleN/dv-classifier/utils.py code served (permissive licence) · get_code("28e6e483d7fbbfac") |
| strings_to_tensors | Ran | LucilleN/dv-classifier/utils.py code served (permissive licence) · get_code("2d46d7a5d33366fd") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Technologies for abusive language detection are being developed and applied with little consideration of their potential biases. We examine racial bias in five different sets of Twitter data annotated for hate speech and abusive language. We train classifiers on these datasets and compare the predictions of these classifiers on tweets written in African-American English with those written in Standard American English. The results show evidence of systematic racial bias in all datasets, as classifiers trained on them tend to predict that tweets written in African-American English are abusive at substantially higher rates. If these abusive language detection systems are used in the field they will therefore have a disproportionate negative impact on African-American social media users. Consequently, these systems may discriminate against the groups who are often the targets of the abuse we are trying to detect.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("1905.12516")
get_code_for_paper("1905.12516")
have("1905.12516")
Connect an agent — have() is free.