Exploring the role of personality traits in followee recommendation

Autores
Tommasel, Antonela; Corbellini, Alejandro; Godoy, Daniela Lis; Schiaffino, Silvia Noemi
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Purpose - Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. To find interesting users to follow, most recommendation systems leverage different factors such as graph topology or user-generated content, among others. They mostly disregard, however, the effect of psychological characteristics, such as personality, over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, this study aims at shedding some light on the impact of personality traits on followee selection. Design/Methodology/Approach - We performed a data analysis comparing the similarity among Twitter users and their followees regarding personality traits. We analysed three different similarity measures. First, we computed an overall similarity considering the five personality traits or dimensions of the Five-Factor model as a whole. Second, we computed dimension-to-dimension similarity considering each individual personality trait independently of each other. Third, we calculated a cross-dimension similarity considering each personality dimension in relation to the others. Findings - This study showed that personality should be considered as a distinctive factor in the process of followee selection. However, personality dimensions should not be analysed as a whole as the overall personality similarity may not accurately assess the actual matching between individuals. Instead, the performed data analysis showed the existence of relations among the individual dimensions. Thus, the importance of considering each personality trait with respect to others is stated. Originality/Value - This study is among the firsts to study the impact of personality, one of the primary factors that influence human behaviour and social relationships, in the selection of followees in micro-blogging communities.
Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Corbellini, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Materia
Followee Recomendation
Recommender Systems
Personality Traits
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/6837
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/6837
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Exploring the role of personality traits in followee recommendationTommasel, AntonelaCorbellini, AlejandroGodoy, Daniela LisSchiaffino, Silvia NoemiFollowee RecomendationRecommender SystemsPersonality Traitshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Purpose - Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. To find interesting users to follow, most recommendation systems leverage different factors such as graph topology or user-generated content, among others. They mostly disregard, however, the effect of psychological characteristics, such as personality, over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, this study aims at shedding some light on the impact of personality traits on followee selection. Design/Methodology/Approach - We performed a data analysis comparing the similarity among Twitter users and their followees regarding personality traits. We analysed three different similarity measures. First, we computed an overall similarity considering the five personality traits or dimensions of the Five-Factor model as a whole. Second, we computed dimension-to-dimension similarity considering each individual personality trait independently of each other. Third, we calculated a cross-dimension similarity considering each personality dimension in relation to the others. Findings - This study showed that personality should be considered as a distinctive factor in the process of followee selection. However, personality dimensions should not be analysed as a whole as the overall personality similarity may not accurately assess the actual matching between individuals. Instead, the performed data analysis showed the existence of relations among the individual dimensions. Thus, the importance of considering each personality trait with respect to others is stated. Originality/Value - This study is among the firsts to study the impact of personality, one of the primary factors that influence human behaviour and social relationships, in the selection of followees in micro-blogging communities.Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Corbellini, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaEmerald Group Publishing Limited2015-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/6837Tommasel, Antonela; Corbellini, Alejandro; Godoy, Daniela Lis; Schiaffino, Silvia Noemi; Exploring the role of personality traits in followee recommendation; Emerald Group Publishing Limited; Online Information Review; 39; 6; 10-2015; 812-8301468-4527enginfo:eu-repo/semantics/altIdentifier/url/http://www.emeraldinsight.com/doi/abs/10.1108/OIR-04-2015-0107info:eu-repo/semantics/altIdentifier/doi/10.1108/OIR-04-2015-0107info:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:05:12Zoai:ri.conicet.gov.ar:11336/6837instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:05:12.573CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Exploring the role of personality traits in followee recommendation
title Exploring the role of personality traits in followee recommendation
spellingShingle Exploring the role of personality traits in followee recommendation
Tommasel, Antonela
Followee Recomendation
Recommender Systems
Personality Traits
title_short Exploring the role of personality traits in followee recommendation
title_full Exploring the role of personality traits in followee recommendation
title_fullStr Exploring the role of personality traits in followee recommendation
title_full_unstemmed Exploring the role of personality traits in followee recommendation
title_sort Exploring the role of personality traits in followee recommendation
dc.creator.none.fl_str_mv Tommasel, Antonela
Corbellini, Alejandro
Godoy, Daniela Lis
Schiaffino, Silvia Noemi
author Tommasel, Antonela
author_facet Tommasel, Antonela
Corbellini, Alejandro
Godoy, Daniela Lis
Schiaffino, Silvia Noemi
author_role author
author2 Corbellini, Alejandro
Godoy, Daniela Lis
Schiaffino, Silvia Noemi
author2_role author
author
author
dc.subject.none.fl_str_mv Followee Recomendation
Recommender Systems
Personality Traits
topic Followee Recomendation
Recommender Systems
Personality Traits
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Purpose - Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. To find interesting users to follow, most recommendation systems leverage different factors such as graph topology or user-generated content, among others. They mostly disregard, however, the effect of psychological characteristics, such as personality, over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, this study aims at shedding some light on the impact of personality traits on followee selection. Design/Methodology/Approach - We performed a data analysis comparing the similarity among Twitter users and their followees regarding personality traits. We analysed three different similarity measures. First, we computed an overall similarity considering the five personality traits or dimensions of the Five-Factor model as a whole. Second, we computed dimension-to-dimension similarity considering each individual personality trait independently of each other. Third, we calculated a cross-dimension similarity considering each personality dimension in relation to the others. Findings - This study showed that personality should be considered as a distinctive factor in the process of followee selection. However, personality dimensions should not be analysed as a whole as the overall personality similarity may not accurately assess the actual matching between individuals. Instead, the performed data analysis showed the existence of relations among the individual dimensions. Thus, the importance of considering each personality trait with respect to others is stated. Originality/Value - This study is among the firsts to study the impact of personality, one of the primary factors that influence human behaviour and social relationships, in the selection of followees in micro-blogging communities.
Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Corbellini, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
description Purpose - Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. To find interesting users to follow, most recommendation systems leverage different factors such as graph topology or user-generated content, among others. They mostly disregard, however, the effect of psychological characteristics, such as personality, over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, this study aims at shedding some light on the impact of personality traits on followee selection. Design/Methodology/Approach - We performed a data analysis comparing the similarity among Twitter users and their followees regarding personality traits. We analysed three different similarity measures. First, we computed an overall similarity considering the five personality traits or dimensions of the Five-Factor model as a whole. Second, we computed dimension-to-dimension similarity considering each individual personality trait independently of each other. Third, we calculated a cross-dimension similarity considering each personality dimension in relation to the others. Findings - This study showed that personality should be considered as a distinctive factor in the process of followee selection. However, personality dimensions should not be analysed as a whole as the overall personality similarity may not accurately assess the actual matching between individuals. Instead, the performed data analysis showed the existence of relations among the individual dimensions. Thus, the importance of considering each personality trait with respect to others is stated. Originality/Value - This study is among the firsts to study the impact of personality, one of the primary factors that influence human behaviour and social relationships, in the selection of followees in micro-blogging communities.
publishDate 2015
dc.date.none.fl_str_mv 2015-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/6837
Tommasel, Antonela; Corbellini, Alejandro; Godoy, Daniela Lis; Schiaffino, Silvia Noemi; Exploring the role of personality traits in followee recommendation; Emerald Group Publishing Limited; Online Information Review; 39; 6; 10-2015; 812-830
1468-4527
url http://hdl.handle.net/11336/6837
identifier_str_mv Tommasel, Antonela; Corbellini, Alejandro; Godoy, Daniela Lis; Schiaffino, Silvia Noemi; Exploring the role of personality traits in followee recommendation; Emerald Group Publishing Limited; Online Information Review; 39; 6; 10-2015; 812-830
1468-4527
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.emeraldinsight.com/doi/abs/10.1108/OIR-04-2015-0107
info:eu-repo/semantics/altIdentifier/doi/10.1108/OIR-04-2015-0107
info:eu-repo/semantics/altIdentifier/doi/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Emerald Group Publishing Limited
publisher.none.fl_str_mv Emerald Group Publishing Limited
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.885934

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