Extracting Human Temporal Orientation from Facebook Language

H. Andrew Schwartz, Gregory Park, Maarten Sap, Evan Weingarten, Johannes Eichstaedt, Margaret Kern, David Stillwell, Michal Kosinski, Jonah Berger, Martin Seligman, Lyle Ungar
2015 Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies  
People vary widely in their temporal orientation-how often they emphasize the past, present, and future-and this affects their finances, health, and happiness. Traditionally, temporal orientation has been assessed by self-report questionnaires. In this paper, we develop a novel behavior-based assessment using human language on Facebook. We first create a past, present, and future message classifier, engineering features and evaluating a variety of classification techniques. Our message
more » ... r achieves an accuracy of 71.8%, compared with 52.8% from the most frequent class and 58.6% from a model based entirely on time expression features. We quantify a users' overall temporal orientation based on their distribution of messages and validate it against known human correlates: conscientiousness, age, and gender. We then explore social scientific questions, finding novel associations with the factors openness to experience, satisfaction with life, depression, IQ, and one's number of friends. Further, demonstrating how one can track orientation over time, we find differences in future orientation around birthdays.
doi:10.3115/v1/n15-1044 dblp:conf/naacl/SchwartzPSWEKSK15 fatcat:aqcs3zq435fpdjihwecom553qi