“Tell me who you are” Latent semantic analysis for analyzing spontaneous self-presentations in different situations
Amato, Clara ; Sikström, Sverker LU
and Garcia, Danilo
(2020)
In TPM - Testing, Psychometrics, Methodology in Applied Psychology
27(2).
p.153-170
- 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 recruitment condition (vs. natural language) had significantly higher number of agentic words (e.g., problem-solver, responsible, able... (More)
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 recruitment 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.
(Less)
- author
- Amato, Clara
; Sikström, Sverker
LU
and Garcia, Danilo
- organization
- publishing date
- 2020-06
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Agency, Communion, Impression management, Latent semantic analysis, Self-presentation
- in
- TPM - Testing, Psychometrics, Methodology in Applied Psychology
- volume
- 27
- issue
- 2
- pages
- 18 pages
- publisher
- Cises Srl
- external identifiers
-
- scopus:85086256200
- ISSN
- 1972-6325
- DOI
- 10.4473/TPM27.2.1
- language
- English
- LU publication?
- yes
- id
- b9f1e749-c10f-43f1-bf39-993df7efc26e
- date added to LUP
- 2021-01-13 09:25:59
- date last changed
- 2022-04-19 03:38:31
@article{b9f1e749-c10f-43f1-bf39-993df7efc26e,
abstract = {{<p>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 recruitment 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.</p>}},
author = {{Amato, Clara and Sikström, Sverker and Garcia, Danilo}},
issn = {{1972-6325}},
keywords = {{Agency; Communion; Impression management; Latent semantic analysis; Self-presentation}},
language = {{eng}},
number = {{2}},
pages = {{153--170}},
publisher = {{Cises Srl}},
series = {{TPM - Testing, Psychometrics, Methodology in Applied Psychology}},
title = {{“Tell me who you are” Latent semantic analysis for analyzing spontaneous self-presentations in different situations}},
url = {{http://dx.doi.org/10.4473/TPM27.2.1}},
doi = {{10.4473/TPM27.2.1}},
volume = {{27}},
year = {{2020}},
}