PageRank-based prediction of award-winning researchers and the impact of citations
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43932548" target="_blank" >RIV/49777513:23520/17:43932548 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1016/j.joi.2017.09.008" target="_blank" >http://dx.doi.org/10.1016/j.joi.2017.09.008</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.joi.2017.09.008" target="_blank" >10.1016/j.joi.2017.09.008</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
PageRank-based prediction of award-winning researchers and the impact of citations
Popis výsledku v původním jazyce
In this article some recent disputes about the usefulness of PageRank-based methods for the task of identifying influential researchers in citation networks are discussed. In particular, it focuses on the performance of these methods in relation to simple citation counts. With the aim of comparing these two classes of ranking methods, we analyze a large citation network of authors based on almost two million computer science papers and apply four PageRank based and citations-based techniques to rank authors by importance throughout the period 1990–2014 on a yearly basis. We use ACM SIGMOD E. F. Codd Innovations Award and ACM A. M. Turing Award winners in our baseline lists of outstanding scientists and define four relevance weighting schemes with some predictive power for the ranking methods to increase the relevance of researchers winning in the future. We conclude that citations-based rankings perform better for Codd Award winners, but PageRank-based methods do so for Turing Award recipients when using absolute ranks and PageRank-based rankings outperform the citations-based techniques for both Codd and Turing Award laureates when relative ranks are considered. However, the two ranking groups show smaller differences if more weight is assigned to the relevance of future awardees.
Název v anglickém jazyce
PageRank-based prediction of award-winning researchers and the impact of citations
Popis výsledku anglicky
In this article some recent disputes about the usefulness of PageRank-based methods for the task of identifying influential researchers in citation networks are discussed. In particular, it focuses on the performance of these methods in relation to simple citation counts. With the aim of comparing these two classes of ranking methods, we analyze a large citation network of authors based on almost two million computer science papers and apply four PageRank based and citations-based techniques to rank authors by importance throughout the period 1990–2014 on a yearly basis. We use ACM SIGMOD E. F. Codd Innovations Award and ACM A. M. Turing Award winners in our baseline lists of outstanding scientists and define four relevance weighting schemes with some predictive power for the ranking methods to increase the relevance of researchers winning in the future. We conclude that citations-based rankings perform better for Codd Award winners, but PageRank-based methods do so for Turing Award recipients when using absolute ranks and PageRank-based rankings outperform the citations-based techniques for both Codd and Turing Award laureates when relative ranks are considered. However, the two ranking groups show smaller differences if more weight is assigned to the relevance of future awardees.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Journal of Informetrics
ISSN
1751-1577
e-ISSN
—
Svazek periodika
11
Číslo periodika v rámci svazku
4
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
25
Strana od-do
1044-1068
Kód UT WoS článku
000418020600010
EID výsledku v databázi Scopus
2-s2.0-85031021034