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Predicting Individual Well-Being Through the Language of Social Media., , , , , , , , , and 3 other author(s). PSB, page 516-527. (2016)Latent Human Traits in the Language of Social Media: An Open-Vocabulary Approach., , , , , , , and . CoRR, (2017)Toward Personality Insights from Language Exploration in Social Media., , , , , , , , and . AAAI Spring Symposium: Analyzing Microtext, volume SS-13-01 of AAAI Technical Report, AAAI, (2013)Choosing the Right Words: Characterizing and Reducing Error of the Word Count Approach., , , , , , , and . *SEM@NAACL-HLT, page 296-305. Association for Computational Linguistics, (2013)Personality, gender, and age in the language of social media: The open-vocabulary approach, , , , , , , , , and 1 other author(s). PloS one, 8 (9): e73791 (2013)Extracting Human Temporal Orientation from Facebook Language., , , , , , , , , and 1 other author(s). HLT-NAACL, page 409-419. The Association for Computational Linguistics, (2015)Towards Assessing Changes in Degree of Depression through Facebook., , , , , , , and . CLPsych@ACL, page 118-125. Association for Computational Linguistics, (2014)Developing Age and Gender Predictive Lexica over Social Media., , , , , , , and . EMNLP, page 1146-1151. ACL, (2014)Characterizing Geographic Variation in Well-Being Using Tweets., , , , , , , , , and 1 other author(s). ICWSM, The AAAI Press, (2013)Estimating geographic subjective well-being from Twitter: A comparison of dictionary and data-driven language methods., , , , , and . Proc. Natl. Acad. Sci. USA, 117 (19): 10165-10171 (2020)