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Linguistic Markers of Intent in Online Dating

This study analyzes linguistic markers of intent in online dating profiles to predict motivations for relationship initiation. It explores various linguistic cues using Linguistic Inquiry and Word Count (LIWC) tool on a dataset of 120 profiles.

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Linguistic Markers of Intent in Online Dating

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  1. Does language choice predict motivations for relationship initiation?: using liwc to analyze linguistic markers of intent in online dating profiles Lieselsharabi David J. Roaché

  2. Rationale • Language as a window into culture (Chung & Pennebaker, 2012) • Advantages of using Linguistic Inquiry and Word Count (LIWC; Pennebaker, Booth, & Francis, 2007) • Large scale language analysis over a variety of platforms • Twitter: Arab spring (Elson et al., 2012), stock market (Grossman, 2010), Germany’s 2009 federal elections (Tumasjan, Sprenger, Sandner, & Welpe, 2010) • Facebook: Gross national happiness index (Kramer, 2010) • Online dating: Deception (Toma & Hancock, 2012; Hancock & Toma, 2009; Toma & Hancock, 2009) • Analyze Words detects personality characteristics

  3. Dataset • Free and popular • Unique set of motivations • Intent (e.g., hang out, intimate encounter) • Looking for (e.g., wants relationship, looking for someone to marry) • No violation of Terms of Service

  4. Research Questions • RQ1: Do linguistic markers predict relational intent on POF? • RQ2: Which linguistic markers will be the best predictors of relational intent on POF?

  5. Method • Online Dating Profiles (N = 120) • Equal numbers of males and females • Equal numbers of profiles from six categories of intent • Looking for a commitment (66.7%; n = 80) • Not looking for a commitment (33.3%; n = 40) • Demographics • Ages ranged from 18 to 61 (M = 33.63; SD = 10.32) • Mostly Caucasian (69.2%; n = 83), followed by Black (17.5%; n = 21), Hispanic (8.3%; n = 10), Mixed Race (1.7%; n = 2), Other (1.7%; n = 2), Asian (.8%; n = 1), and Native American (.8%; n = 1) • Data Analysis • Linguistic Inquiry and Word Count (LIWC) (Pennebaker, Booth, & Francis, 2007) • Stepwise logistic regression with forward selection

  6. Results

  7. Thank you

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