title: From "Sooo excited!!!" to "So proud": using language to study development.
abstract: We introduce a new method, differential language analysis (DLA), for studying human development in which computational linguistics are used to analyze the big data available through online social media in light of psychological theory. Our open vocabulary DLA approach finds words, phrases, and topics that distinguish groups of people based on 1 or more characteristics. Using a data set of over 70,000 Facebook users, we identify how word and topic use vary as a function of age and compile cohort specific words and phrases into visual summaries that are face valid and intuitively meaningful. We demonstrate how this methodology can be used to test developmental hypotheses, using the aging positivity effect (Carstensen & Mikels, 2005) as an example. While in this study we focused primarily on common trends across age-related cohorts, the same methodology can be used to explore heterogeneity within developmental stages or to explore other characteristics that differentiate groups of people. Our comprehensive list of words and topics is available on our web site for deeper exploration by the research community.
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Margaret L
authors.initials: ML
authors.lastname: Kern
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Johannes C
authors.initials: JC
authors.lastname: Eichstaedt
authors.affiliation: Department of Computer and Information Science, University of Pennsylvania.
authors.forename: H Andrew
authors.initials: HA
authors.lastname: Schwartz
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Gregory
authors.initials: G
authors.lastname: Park
authors.affiliation: Department of Computer and Information Science, University of Pennsylvania.
authors.forename: Lyle H
authors.initials: LH
authors.lastname: Ungar
authors.affiliation: Psychometrics Centre, University of Cambridge.
authors.forename: David J
authors.initials: DJ
authors.lastname: Stillwell
authors.affiliation: Psychometrics Centre, University of Cambridge.
authors.forename: Michal
authors.initials: M
authors.lastname: Kosinski
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Lukasz
authors.initials: L
authors.lastname: Dziurzynski
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Martin E P
authors.initials: ME
authors.lastname: Seligman
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000375:Aging; D004644:Emotions; D005260:Female; D006803:Human Development; D006801:Humans; D007802:Language; D008297:Male; D008875:Middle Aged; D011582:Psychological Theory; D012737:Sex Factors; D061108:Social Media; D013223:Statistics as Topic; D014825:Vocabulary; D055815:Young Adult