User-Level Race and Ethnicity Predictors from Twitter Text
We develop predictive models from text which accurately predict the membership of a user to the four largest racial and ethnic groups with up to . 884 AUC and make these available to the research community.
In this study, we introduce a new data set where user-level race and ethnicity labels are collected through an online survey of Twitter users. We build models ...
Models for predicting user race from tweets for the four most important US racial/ethnic groups. - Adding name information improves text-based prediction.
A data set of users who self-report their race/ethnicity through a survey is introduced, in contrast to previous approaches that use distantly supervised ...
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Social media analysis frequently requires tools that can automatically infer demographics to contextualize trends. These tools often require.
We present a scoping review to identify methods used to extract the race or ethnicity of Twitter users from Twitter data sets.
User-Level Race and Ethnicity Predictors from Twitter Text. D Preotiuc-Pietro, L Ungar. COLING, 2018. 94, 2018. Predicting and Characterising User Impact on ...
Ethnicity identification. Ethnicity is estimated using the Python package ethnicolr which uses character-level RNN to predict race from first and last name.
Mar 8, 2024 · User- level race and ethnicity predictors from twitter text. In Proceedings of the 27th international conference on computational ...
In this paper, we fit regression models to predict seven demographic variables of Twitter users (age, gender, education, ethnicity, income, parental status, and ...