Personality extraction through LinkedIn
dc.contributor.advisor | Langlais, Philippe | |
dc.contributor.advisor | Lapalme, Guy | |
dc.contributor.author | Piedboeuf, Frédéric | |
dc.date.accessioned | 2019-11-19T19:23:16Z | |
dc.date.available | NO_RESTRICTION | fr |
dc.date.available | 2019-11-19T19:23:16Z | |
dc.date.issued | 2019-10-30 | |
dc.date.submitted | 2019-05 | |
dc.identifier.uri | http://hdl.handle.net/1866/22536 | |
dc.subject | Extraction de personalité | fr |
dc.subject | MBTI | fr |
dc.subject | DiSC | fr |
dc.subject | fr | |
dc.subject | Réseau sociaux | fr |
dc.subject | Profilage d'auteur | fr |
dc.subject | Personality Extraction | fr |
dc.subject | Social Network | fr |
dc.subject | Author Profiling | fr |
dc.subject.other | Applied Sciences - Computer Science / Sciences appliqués et technologie - Informatique (UMI : 0984) | fr |
dc.title | Personality extraction through LinkedIn | fr |
dc.type | Thèse ou mémoire / Thesis or Dissertation | |
etd.degree.discipline | Informatique | fr |
etd.degree.grantor | Université de Montréal | fr |
etd.degree.level | Maîtrise / Master's | fr |
etd.degree.name | M. Sc. | fr |
dcterms.abstract | L'extraction de personnalité sur les réseaux sociaux est un domaine qui n'a que récemment commencé à capturer l'attention des chercheurs. La tâche consiste à, en partant d'un corpus de profils d'utilisateurs de réseaux sociaux, être capable de classifier leur personnalité correctement, selon un modèle de personnalité tel que défini en psychologie. Ce mémoire apporte trois innovations au domaine. Premièrement, la collecte d'un corpus d'utilisateurs LinkedIn. Deuxièmement, l'extraction sur deux modèles de personnalités, MBTI et DiSC, l'extraction sur DiSC n'ayant pas encore été faite dans le domaine, et finalement, la possibilité de passer d'un modèle de personnalité à l'autre est explorée, dans l'idée qu'il serait ainsi possible d'obtenir les résultats de multiples modèles de personnalités en partant d'un seul test. | fr |
dcterms.abstract | Personality extraction through social networks is a field that only recently started to capture the attention of researchers. The task consists in, starting with a corpus of user profiles on a particular social network, classifying their personalities correctly, according to a specific personality model as described in psychology. In this master thesis, three innovations to the domain are presented. Firstly, the collection of a corpus of LinkedIn users. Secondly, the extraction of the personality according to two personality models, DiSC and MBTI, the extraction with DiSC having never been done before. Lastly, the idea of going from one personality model to the other is explored, thus creating the possibility of having the results on two personality models with only one personality test. | fr |
dcterms.language | eng | fr |
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