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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 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 • Implications/Ethics
Faces are privileged… • Innate ability to recognize and discriminate • Brain modules dedicated to face processing • Nonverbal Behavior accounts for a majority of human communication
Non-Verbal Cues in Politics • Substantive Information deemed paramount • Policy positions • Performance records • Partisan affiliation • Physical cues considered secondary • Some notable Exceptions…
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)
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
“Facial Competence” wins actual elections(Todorov and colleagues, 2004, 2005) Subjects rated “competence” of candidates
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)
Transformed Social Interaction (TSI) Actual Behavior Strategic Filter Transformed Behavior
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)
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
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
Held Constant • Voter Gender • Voter Party
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.
Preference Score Candidate Score = Affect + Traits + Thermometer + Voting Overall Preference = Bush Score – Kerry Score High Score = Bush Preference Low Score = Kerry Preference
Study TwoComparing Cues • Facial Similarity • Candidate Familiarity • Ideological Similarity • Party Similarity • Gender Similarity • Which of these cues take precedence? Single Candidate Presentation Online
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 • ???
Analysis • Factors • Facial Similarity • Candidate Familiarity • Party Similarity • Ideological Similarity • Gender Similarity • Covariate • Education • Measure • Overall Preference Score
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.
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.
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)