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Transformed Facial Similarity and Social Influence

Transformed Facial Similarity and Social Influence. Jeremy Bailenson, Shanto Iyengar, & Nick Yee Stanford University. Overview. Nonverbal evaluation of leaders Facial similarity as an influence heuristic Transformations in digital mass media Experimental evidence from Election Studies

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Transformed Facial Similarity and Social Influence

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  1. Transformed Facial Similarity and Social Influence Jeremy Bailenson, Shanto Iyengar, & Nick Yee Stanford University

  2. Overview • Nonverbal evaluation of leaders • Facial similarity as an influence heuristic • Transformations in digital mass media • Experimental evidence from Election Studies • Implications/Ethics

  3. Faces are privileged… • Innate ability to recognize and discriminate • Brain modules dedicated to face processing • Nonverbal Behavior accounts for a majority of human communication

  4. Non-Verbal Cues in Politics • Substantive Information deemed paramount • Policy positions • Performance records • Partisan affiliation • Physical cues considered secondary • Some notable Exceptions…

  5. Televised versus Radio broadcasts… 1960 1st Presidential Debate “Kennedy was bronzed beautifully . . . Nixon looked like death.” (Stanton, 2000, President of CBS) Nixon fares much better for radio listeners than TV listeners, (for a recent replication see Druckman, 1993)

  6. Nonverbally Attractive Candidates Win Elections(Rosenberg, Bohan; McCafferty; & Harris, 1986) • Subjects rated “congressional demeanor of fictitious candidates” • Candidates chosen for high/low nonverbal demeanor: -attractiveness -nonverbal gestures -dress • High candidates win 60 percent of the vote

  7. “Facial Competence” wins actual elections(Todorov and colleagues, 2004, 2005) Subjects rated “competence” of candidates

  8. Competence via similarity… Similarity among people results in: • Attraction (Shanteau & Nagy, 1979) • More Persuasion (Chaiken, 1979) • More purchases (Brock, 1965) • More altruistic helping behavior (Dovidio, 1984) • Trust (DeBruine, 2002)

  9. A World of Digital Mass Media….

  10. Transformed Social Interaction (TSI) Actual Behavior Strategic Filter Transformed Behavior

  11. Facial Identity Capture

  12. Morph Examples

  13. Overview of Experiments • Study 1: Facial similarity of unfamiliar candidates • Study 2: Facial Similarity of familiar candidates • Study 3: Pitting Familiarity against Similarity • Study 4: Explicating similarity (facial, partisan, issue)

  14. Photo Criteria • Rejected if: • Wearing glasses • Have facial hair • Taken in bad lighting conditions • Not facing camera • Strange facial expressions • Low resolution (less than 350 x 350) • Blurred or other optical artifacts

  15. Measures • Affective Response • Has this candidate ever made you feel … (Angry, Proud, Disgusted, Hopeful, Afraid)? • Trait Ratings • How well does this label describe the candidate … (Dishonest, Moral, Intelligent, etc.)? • Feeling Thermometer • Intention to Vote

  16. Held Constant • Voter Gender • Voter Party

  17. Study OneDoes Facial Similarity Matter? Split Panel Presentation in a web-based survey. N = 160 Average Age = 41.1 SD Age = 14.8 Half morphed with Bush; Half morphed with Kerry.

  18. Morph Example

  19. Preference Score Candidate Score = Affect + Traits + Thermometer + Voting Overall Preference = Bush Score – Kerry Score High Score = Bush Preference Low Score = Kerry Preference

  20. Study TwoComparing Cues • Facial Similarity • Candidate Familiarity • Ideological Similarity • Party Similarity • Gender Similarity • Which of these cues take precedence? Single Candidate Presentation Online

  21. Selected Candidates

  22. Selected Candidates

  23. Ideological Similarity • Troop Withdrawal • Should we set a time-table for troop withdrawal from Iraq?(3 months, 6 months, 1 year, 2 years, 3-5 years, and no time limit) • Overseas Outsourcing • ???

  24. Analysis • Factors • Facial Similarity • Candidate Familiarity • Party Similarity • Ideological Similarity • Gender Similarity • Covariate • Education • Measure • Overall Preference Score

  25. Results • Main effect of Party Similarity (p < .001, 2 = .05) • Favored own party. • Main effect of Policy Similarity (p = .007, 2 = .02) • Favored candidates with similar policies. • Main effect of Candidate Familiarity (p = .001, 2 = .03) • Favored familiar candidates.

  26. Study ThreeTesting Terror Management Split Panel Presentation in a web-based survey. N = 105 Average Age = 51.0 SD Age = 11.6 Half morphed with Crist; Half morphed with Davis.

  27. Results • Series of T-Tests on Measures: • Traits (t[71] = -3.24, p = .002, r = .36) • Thermometer (t[71] = -2.62, p = .01) • Voting Intention (t[71] = -2.02, p = .05, r = .23) • Affect (t[71] = .67, p = .51, r = .08)

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