2 research outputs found
Personality extraction through LinkedIn
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.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
The state of OAI-PMH repositories in Canadian Universities
This article presents a study of the current state of Universities
Institutional Repositories (UIRs) in Canada. UIRs are vital to sharing
information and documents, mainly Electronic Thesis and Dissertation (ETDs),
and theoretically allow anyone, anywhere, to access the documents contained
within the repository. Despite calls for consistent and shareable metadata in
these repositories, our literature review shows inconsistencies in UIRs,
including incorrect use of metadata fields and the omission of crucial
information, rendering the systematic analysis of UIR complex. Nonetheless, we
collected the data of 57 Canadian UIRs with the aim of analyzing Canadian data
and to assess the quality of its UIRs. This was surprisingly difficult due to
the lack of information about the UIRs, and we attempt to ease future
collection efforts by organizing vital information which are difficult to find,
starting from addresses of UIRs. We furthermore present and analyze the main
characteristics of the UIRs we managed to collect, using this dataset to create
recommendations for future practitioners.Comment: Published at DCMI -- International conference on dublin core and
metadata applications, 202