%0 Conference Paper %A Evans, Tim %A Anthony, Hannah %A Goldberg, Sophia %D 2015 %T The Formation of the Citation Network from Global and Local Knowledge %U https://figshare.com/articles/poster/Do_We_Need_Global_and_Local_Knowledge_of_the_Citation_Network/1452953 %R 10.6084/m9.figshare.1452953.v3 %2 https://ndownloader.figshare.com/files/2126232 %K Bibliometrics %K citation analysis %K citation network %K scientometrics %K complexity %K Statistics %K Condensed Matter Physics %K Sociology %X

This is the A0 size poster for the ISSI 2015 meeting Boğaziçi University in Istanbul, 29th June - 3rd July.  This poster is based on a longer paper in Scientometrics and below is a link to arXiv of the first version of this full paper.

A short two page summary of the work in this poster and in the full paper is publsihed in the ISSI proceedings.  The following is the citation data for this proceedings paper along with its abstract. 

Goldberg, S.; Anthony, H. & Evans, T.S.

Salah, A. A.; Tonta, Y.; Salah, A. A. A.; Sugimoto, C. & Al, U. (Eds.)
Do We Need Global and Local Knowledge of the Citation Network?
Proceedings of ISSI 2015 Istanbul: 15th International Society of Scientometrics and Informetrics Conference, Istanbul, Turkey, 29 June to 3 July, 2015, 2015, 282-283

Abstract: The distribution of the number of academic publications as a function of citation count for those papers published in any one year is known to be remarkably similar from year to year. In particular the width of these distributions, defined using a partial lognormal fit, is roughly constant. In this poster we show that simple citation models fail to capture this behaviour. We then provide a simple three parameter citation network model using a mixture of local and global search processes which can reproduce the correct distribution over time. We use the citation network of papers from the hep-th section of arXiv to test our model. For this data, around 20% of citations use global information to reference recently published papers, while the remaining 80% are found using local searches.

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