In this paper we focus on the connection between age and language use, exploring age prediction of Twitter users based on their tweets. We discuss the construction of a fine-grained annotation effort to assign ages and life stages to Twitter users. Using this dataset, we explore age prediction in three different ways: classifying users into age categories, by life stages, and predicting their exact age. We find that an automatic system achieves better performance than humans on these tasks and that both humans and the automatic systems have difficulties predicting the age of older people. Moreover, we present a detailed analysis of variables that change with age. We find strong patterns of change, and that most changes occur at young ages.
|Title of host publication||Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media, ICWSM 2013|
|Place of Publication||Palo Alto, CA, USA|
|Number of pages||10|
|Publication status||Published - Jul 2013|
|Event||7th International AAAI Conference on Weblogs and Social Media, ICWSM 2013 - Cambridge, United States|
Duration: 8 Jul 2013 → 10 Jul 2013
Conference number: 7
|Conference||7th International AAAI Conference on Weblogs and Social Media, ICWSM 2013|
|Period||8/07/13 → 10/07/13|
Nguyen, D-P., Gravel, R., Trieschnigg, R. B., & Meder, T. (2013). "How old do you think I am?": A study of language and age in Twitter. In Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media, ICWSM 2013 (pp. 439-448). Palo Alto, CA, USA: AAAI Press.