Conference Proceedings

Extracting human temporal orientation from Facebook language

HA Schwartz, GJ Park, M Sap, E Weingarten, J Eichstaedt, ML Kern, D Stillwell, M Kosinski, J Berger, M Seligman, LH Ungar

NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference | Published : 2015


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 classifier 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 b..

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