Show simple item record

dc.contributor.authorCiotti, Valerio
dc.date.accessioned2018-01-29T14:34:21Z
dc.date.available2018-01-29T14:34:21Z
dc.date.issued2018-01-17
dc.date.submitted2018-01-29T11:00:16.155Z
dc.identifier.citationCiotti, V. 2018. Positive and negative connections and homophily in complex networks. Queen Mary University of Londonen_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/31787
dc.descriptionPhDen_US
dc.description.abstractIn this thesis I investigate the effects of positive and negative connections on social and organization networks, and the presence and role of homophily in networks of scientific collaborations and citations through the combination of methodologies borrowed from complexity science, statistics, and organizational sciences. In the first part of the thesis, I study the differences between patterns of positive and negative connections among individuals in two online signed social networks. Findings suggest that the sign of links in a social network shapes differently the network's topology: there is a positive correlation between the degrees of two nodes, when they share a positive connection, and a negative correlation when they share a negative connection. I then move my focus to the study of a dataset on start-ups from which I construct and analyse the competition and mobility networks among companies. Results show that the presence of competition has negative effects on the mobility of people among companies and on the success of the start-up ecosystem of a nation. Competitive behaviours may also emerge in science. Therefore, in the second part of this thesis, I focus on a database of all papers and authors who have published in the American Physical Society (APS) journals. Through the analysis of the citation network of the APS, I propose a method that aims to statistically validate the presence (or absence) of a citation between any two articles. Results show that homophily is an important mechanism behind the citation between articles: the more two articles share similar bibliographies, i.e., deal with similar arguments, the more likely there is a citation between them. In the last chapter, I investigate the presence of homophily in the APS data set, this time at the level of the collaboration network among sci- entists. Results show that homophily can be responsible in fostering collaboration, but above a given point the effect of similarity decreases the probability of a collaboration. Additionally, I propose a model that successfully reproduces the empirical findings.en_US
dc.language.isoenen_US
dc.publisherQueen Mary University of Londonen_US
dc.rightsThe copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author
dc.subjectMathematical Sciencesen_US
dc.subjectsocial and organization networksen_US
dc.subjecthomophilyen_US
dc.subjectnetwork studiesen_US
dc.titlePositive and negative connections and homophily in complex networksen_US
dc.typeThesisen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

  • Theses [4235]
    Theses Awarded by Queen Mary University of London

Show simple item record