Paper: Why Gender and Age Prediction from Tweets is Hard: Lessons from a Crowdsourcing Experiment

ACL ID C14-1184
Title Why Gender and Age Prediction from Tweets is Hard: Lessons from a Crowdsourcing Experiment
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

There is a growing interest in automatically predicting the gender and age of authors from texts. However, most research so far ignores that language use is related to the social identity of speak- ers, which may be different from their biological identity. In this paper, we combine insights from sociolinguistics with data collected through an online game, to underline the importance of approaching age and gender as social variables rather than static biological variables. In our game, thousands of players guessed the gender and age of Twitter users based on tweets alone. We show that more than 10% of the Twitter users do not employ language that the crowd as- sociates with their biological sex. It is also shown that older Twitter users are often perceived to be younger. Our findings highl...