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Mryglod Olesya

Mryglod Olesya


By olesya - Posted on 07 October 2010

Mryglod O.
Department: 
Laboratory for Statistical Physics of Complex Systems
Position: 
Researcher
Title: 
PhD (Information Technologies)
Brief info: 

The scientific interests are mainly connected with the analysis of scientometrical and social objects.
 
Some examples are:
 

  • analysis of bibliographic information to describe the set of scientific journals (their interrelations, topical landscape etc.)

We use several approaches to analyse a scientific journal as a complex system and to make a possibly more complete description of its current state and evolution. Methods of complex networks theory, statistics, and queueing theory are used. In particular, we construct and analyse different kinds of complex networks based on co-authorship data, information about the common PACS numbers etc. We analyse the priorities of scientific trends reflected in the journal and its international collaboration landscape. Moreover, to characterize an efficiency of the paper processing, we study the time dynamics of editorial processing in terms of queueing theory and human activity analysis.
 

  • analysis of correlations between peer-review based scores and citations
    based scores on a departmental level

Many different measures are used to assess academic research excellence and these are subject to ongoing discussion and debate within the scientometric, universitymanagement and policy-making communities internationally. One topic of continued importance is the extent to which citation-based indicators compare with peer-reviewbased evaluation. We compare estimates for past institutional research performances coming from two bibliometric indicators to the results of the UK’s Research Excellence Framework (former Research Assessment Exercise). In particular, we demonstrate that a version of the departmental h-index is better correlated with the actual results of that peer-review exercise than a competing metric known as the normalised citation-based indicator, However, the similarities are not good enough to make accurate predictions.
 

  • downloads statistics analysis

While peer review and citations reflect opinion about a paper’s quality and scientific impact after reading, downloads rather reflect interest beforehand. In other words, in addition to popularity and prestige, papers may be distinguished by their attractiveness. We consider the download statistics of scientific publications in orde to find typical downloading patterns, "downloads aging" law, etc.

  • quantitative analysis of social systems

Studying human behaviour in virtual environments provides extraordinary opportunities for a quantitative analysis of social phenomena with levels of accuracy that approach those of the natural sciences. We use records of player activities in the massive multiplayer online game Pardus over 1,238 consecutive days, and analyze dynamical features of sequences of actions of players. This study of multi-level human activity can be seen as a dynamic counterpart of static multiplex network analysis. We analyse the time-properties of player's behaviour, showing, that players do not act uniformly but demonstrate peaks of activity separated by periods of inactivity.

  • terms identification in scientific publications (in progress)

 

Scientific interests: 
complex systems, scientometrics, data mining
Recent papers: 
Mryglod O., Kenna R., Holovatch Yu. Is your EPL attractive? Classification of publications through download statistics // EPL. – 2014. - 108. - 50011 [http://arxiv.org/pdf/1409.7889.pdf]
Mryglod O., Kenna R., Holovatch Yu., Berche B. Predicting Results of the Research Excellence Framework using departmental h-Index // Scientometrics. – 2014. – Vol. DOI 10.1007/s11192-014-1512-3. [http://arxiv.org/pdf/1411.1996.pdf]
Mryglod O., Fuchs B., Szell M., Holovatch Yu., Thurner S. Interevent time distributions of human multi-level activity in a virtual world // Physica A. – 2014. – Vol. 419. – P. 681–690, DOI: 10.1007/s11192-012-0874-7. [http://arxiv.org/pdf/1407.2006.pdf]
Мриглод О., Кенна Р., Головач Ю., Берш Б. Про порівняння екстенсивної та інтенсивної мір ефективності наукових груп // Доповіді НАН України. – 2014. – № 3. – С. 75. [http://www.icmp.lviv.ua/sites/default/files/preprints/pdf/1305U.pdf]
Mryglod O., Kenna R., Holovatch Yu., Berche B. Absolute and specific measures of research group excellence // Scientometrics. – 2013. – Vol. 95, Issue 1. – P. 115-127, DOI: 10.1007/s11192-012-0874-7. [http://arxiv.org/pdf/1210.0732.pdf]
e-mail: 
olesya[REPLACE_THIS_WITH_AT_SIGN]icmp.lviv.ua
Tel.: 
+38-032-2761978