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“Tell Me Who You Are" Latent Semantic Analysis for Analyzing Spontaneous Self-Presentations in Different Situations

Journal article
Authors Clara Amato
Sverker Sikström
Danilo Garcia
Published in Testing, Psychometrics, Methodology in Applied Psychology
Volume 27
Issue 2
Pages 153-170
ISSN 1972-6325  
Publication year 2020
Published at Department of Psychology
Pages 153-170
Language en
Links https://www.tpmap.org/tell-me-who-y...
Keywords Latent Semantic Analysis, Agency, Communion, Self-Presentation, Impression Management
Subject categories Applied Psychology, Psychology

Abstract

The aim of the study was to analyze freely generated self-presentations through the natural language processing technique of Latent Semantic Analysis (LSA). Four hundred fifty-one participants (F = 360; M = 143) recruited from LinkedIn (a professional social network) were randomly assigned to generate 10 words to describe themselves to either an employer (recruitment-condition) or a friend (friendship- condition). The words’ frequency-rate and their semantic representation were compared between condi- tions and to the natural language (Google’s n-gram database). Self-presentations produced in the recruit- ment condition (vs. natural language) had significantly higher number of agentic words (e.g., problem- solver, responsible, able team-worker) and their contents were semantically closer to the concept of agency (i.e., competence, assertiveness, decisiveness) comparing to the friendship condition. Further- more, the valence of the self-presentations’ words was higher (i.e., with a more positive meaning) in the recruitment condition. Altogether, these findings are consistent with the literature on the “Big Two,” self- presentation, and impression management.

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