Posts tagged ‘online social networks’

Online Social Network-dataset now available

Online SocialThe Online Social Network-dataset used in my Ph.D. thesis is now available on the Dataset-page. This network has also been described in Patterns and Dynamics of Users’ Behaviour and Interaction: Network Analysis of an Online Community and used in Prominence and control: The weighted rich-club effect and Clustering in weighted networks. The network originate from an online social network among students at University of California, Irvine. The edgelist includes the users that sent or received at least one message during that period (1,899). A total number of 59,835 online messages were sent among these over 20,296 directed ties.

The content of this post has been integrated in the tnet manual, see Datasets.

November 10, 2009 at 5:46 pm

Similarity between node degree and node strength

Correlation between node degree and node strengthThis post explores the relationship between node degree and node strength in an online social network. In the online social network, heterogeneity in nodes’ average tie weight across different levels of degree had been reported. Although degree and average tie weight are significantly correlated, this post argues for the similarity of degree and node strength. In particular, high pair-wise correlation between degree and strength is found. In addition, power-law exponents of degree distributions and strength distribution are reported. The exponents are strikingly similar, in fact, they are almost identical.

Continue Reading October 16, 2009 at 12:57 pm Leave a comment

Thesis: Structure and Evolution of Weighted Networks

I have now completed my Ph.D. at the School of Business and Management of Queen Mary College, University of London. My Ph.D. programme was defined around a number of projects, which drew on, and extended, recent theoretical and methodological advances in network science. The projects that were concerned with weighted networks and longitudinal networks were outlined and critically discussed in my thesis (Structure and Evolution of Weighted Networks). The entire thesis, except Appendix C which is outdated, is available on the Publication > Thesis-page.

Acknowledgements

The theme of this thesis is interdependence among elements. In fact, this thesis is not just a product of myself, but also of my interdependence with others. Without the support of a number of people, it would not have been possible to write. It is my pleasure to have the opportunity to express my gratitude to many of them here.

For my academic achievements, I would like to acknowledge the constant support from my supervisors. In particular, I thank Pietro Panzarasa for taking an active part of all the projects I have worked on. I have also had the pleasure to collaborate with people other than my supervisors. I worked with Vittoria Colizza and Jose J. Ramasco on the analysis and method presented in Chapter 2, Kathleen M. Carley on an empirical analysis of the online social network used throughout this thesis, and Martha J. Prevezer on a project related to knowledge transfer in emerging countries. In addition to these direct collaborations, I would also like to thank Filip Agneessens, Sinan Aral, Steve Borgatti, Ronald Burt, Mauro Faccioni Filho, Thomas Friemel, John Skvoretz, and Vanina Torlo for encouragement and helpful advice. In particular, I would like to thank Tom A. B. Snijders and Klaus Nielsen for insightful reading of this thesis and many productive remarks and suggestions. I have also received feedback on my work at a number of conferences and workshops. I would like to express my gratitude to the participants at these.

On a social note, I would like to thank John, Claudius, and my family for their continuing support. Without them I would have lost focus. My peers and the administrative staff have also been a great source of support. In particular, I would like to extend my acknowledgements to Mariusz Jarmuzek, Geraldine Marks, Roland Miller, Jenny Murphy, Cathrine Seierstad, Lorna Soar, Steven Telford, and Eshref Trushin.

May 15, 2009 at 12:00 am

The importance of allowing ties to decay

Evolving networkRecently, a number of network dataset have been constructed from archival data (e.g., email logs) with the aim to study human interaction. This has allowed researchers to study large-scale social networks. If the archival data does not included information about the severing or weakening of ties, non-relevant interaction among people, which occurred far in the past, might be deemed relevant. This post highlights this issue and suggests imposing a lifespan on interactions to record only relevant ties with the current strength.

The content of this post has been integrated in the tnet manual, see Sliding Window.

March 20, 2009 at 12:00 am


@toreopsahl on Twitter

Error: Please make sure the Twitter account is public.

Licensing

The information on this blog is published under the Creative Commons Attribution-Noncommercial 3.0-lisence.

This means that you are free to:
· share
· adapt
under the following conditions:
· attribution (cite it)
· noncommercial (email me).

Creative Commons License