Crowdsourcing Gender and Age Annotator Rationales in Multiple Languages
Rationales - targeted annotator feedback regarding why and how
they chose a particular annotation collected via crowdsourcing.
We collected rationale annotations from a set of Twitter profiles with known to us (but not known to the annotators)
gender, age and political preference labels and used these
"gold-standard" labels as a quality control check during the rationale annotation.
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