Towards Automated Personality Identification Using Speech Acts

Proceedings of the International AAAI Conference on Web and Social Media, 7

Volume

Vol. 7 No. 2 (2013): ICWSM Workshop Technical Report WS-13-01 (Computational Personality Recognition — Shared Task)

Computational Personality Recognition

The way people communicate — be it verbally, visually, or via text– is indicative of personality traits. In social media the concept of the status update is used for individuals to communicate to their social networks in an always-on fashion. In doing so individuals utilize various kinds of speech acts that, while primarily communicating their content, also leave traces of their personality dimensions behind. We human-coded a set of Facebook status updates from the myPersonality dataset in terms of speech acts label and then experimented with surface level linguistic features including lexical, syntactic, and simple sentiment detection to automatically label status updates as their appropriate speech act. We apply supervised learning to the dataset and using our features are able to classify with high accuracy two dominant kinds of acts that have been found to occur in social media. At the same time we used the coded data to perform a regression analysis to determine which speech acts are significant of certain personality dimensions. The implications of our work allow for automatic large-scale personality identification through social media status updates.

10.1609/icwsm.v7i2.14469