Spontaneous Inference of Personality Traits and Effects on Memory for Online Profiles

Slide 1: Automatic Trait Inferences about Profiles Kristin Stecher & Scott Counts

Slide 2: the new self-representation

Slide 3:  Automatic Trait Inferences ◦ Evidence from social psychology  Automatic inferences of traits (Uleman, 1988) ◦ Behavior  Jack told his mother that he ate the chocolates. ◦ Trait cues recognized faster than semantic cues.  Honest  Chocolates Background Uleman, 1988

Slide 4:  Hypotheses:  Individuals make personality trait inferences when viewing online profiles. ◦ Memory for profiles is based more on the inferences they make from profiles rather than the actual content of the profiles.  These inferences can be “automatic”. Study 1 Automatic Trait Inferences

Slide 5: Automatic trait inferences: 1. Often below conscious awareness. 2. They are not intentional (not implied by the direction set). 3. They are not controllable. Automaticity Uleman, 1999

Slide 6: Created 60 profiles using pilot testing.  Picture +“About me” ◦ 30 trait profiles ◦ 30 semantic (no trait implied) profiles Creating Profiles

Slide 7: Sample Trait Profile (implies hick)

Slide 8: Sample Semantic Profile (does not imply hick)

Slide 9:  Presentation Phase ◦ Trait Profile ◦ Semantic Profile  Cue Phase ◦ Trait Cue  “Hick” ◦ Semantic Cue  “Jordan”  Dependent measure is recall for profile content when cued. Automatic Inferences Methods

Slide 10: Main Effect Profile: F(1,30)=21.4, p<0.001 Profile x Word Interaction: F(1, 29)=35.3, p<0.001 Evidence for Automatic Inferences 31 participants

Slide 11:  Participants remember trait implying profiles better than semantic profiles.  They recall more about implied traits than actual profile content.  ONLY if the profile cues a trait. ◦ i.e. Trait not semantic condition  What are the factors about the profile that affect memory? Discussion

Slide 12:  Overall Coherence: How well do profile elements fit together  Number of Attributes: How many particular elements does a profile contain  Specificity: How specific is each particular element Study 2 Factors that Affect Memory N=3,9,3

Slide 13:  There is a positive relationship between coherence and memory for a profile Coherence Hypotheses

Slide 14: Relationship between profile coherency ratings and memory  Weak to moderate Overall Trait Semantic correlation between profile profile overall coherence and R = .19 .22 .12 memory

Slide 15: Relationship between number of elements and memory R = -.28 R = .33

Slide 16: Specificity Results  Very little Overall Trait Semantic relationship between profile profile specificity and R = -.09 -.16 -.04 memory

Slide 17: Specificity: Individual Differences

Slide 18:  Help users convey traits (30% memory improvement)  Particularly with few elements  Particularly with coherent profiles  Trait tags?  Language processing?  Coherency: General trend of facilitating memory  Try to account for individual differences  Auto-classification of users based on memory preferences (e.g., for specificity)? Summary/Recommendations

Slide 19: Questions? Automatic Trait Inferences about Profiles Kristin Stecher & Scott Counts