Senanayake Upul, Piraveenan Mahendra, Zomaya Albert
Centre for Complex Systems Research, Faculty of Engineering and IT, The University of Sydney, NSW 2006, Australia.
Centre for Distributed and High Performance Computing, School of Information Technologies, The University of Sydney, NSW 2006, Australia.
PLoS One. 2015 Aug 19;10(8):e0134794. doi: 10.1371/journal.pone.0134794. eCollection 2015.
Quantifying and comparing the scientific output of researchers has become critical for governments, funding agencies and universities. Comparison by reputation and direct assessment of contributions to the field is no longer possible, as the number of scientists increases and traditional definitions about scientific fields become blurred. The h-index is often used for comparing scientists, but has several well-documented shortcomings. In this paper, we introduce a new index for measuring and comparing the publication records of scientists: the pagerank-index (symbolised as π). The index uses a version of pagerank algorithm and the citation networks of papers in its computation, and is fundamentally different from the existing variants of h-index because it considers not only the number of citations but also the actual impact of each citation. We adapt two approaches to demonstrate the utility of the new index. Firstly, we use a simulation model of a community of authors, whereby we create various 'groups' of authors which are different from each other in inherent publication habits, to show that the pagerank-index is fairer than the existing indices in three distinct scenarios: (i) when authors try to 'massage' their index by publishing papers in low-quality outlets primarily to self-cite other papers (ii) when authors collaborate in large groups in order to obtain more authorships (iii) when authors spend most of their time in producing genuine but low quality publications that would massage their index. Secondly, we undertake two real world case studies: (i) the evolving author community of quantum game theory, as defined by Google Scholar (ii) a snapshot of the high energy physics (HEP) theory research community in arXiv. In both case studies, we find that the list of top authors vary very significantly when h-index and pagerank-index are used for comparison. We show that in both cases, authors who have collaborated in large groups and/or published less impactful papers tend to be comparatively favoured by the h-index, whereas the pagerank-index highlights authors who have made a relatively small number of definitive contributions, or written papers which served to highlight the link between diverse disciplines, or typically worked in smaller groups. Thus, we argue that the pagerank-index is an inherently fairer and more nuanced metric to quantify the publication records of scientists compared to existing measures.
对政府、资助机构和大学而言,量化和比较研究人员的科研产出已变得至关重要。随着科学家数量的增加以及科学领域的传统定义变得模糊,通过声誉进行比较以及直接评估对该领域的贡献已不再可行。h指数常被用于比较科学家,但存在一些有充分记录的缺点。在本文中,我们引入一种用于衡量和比较科学家发表记录的新指数:网页排名指数(用符号π表示)。该指数在计算中使用了一种网页排名算法版本和论文的引用网络,并且与现有的h指数变体有根本不同,因为它不仅考虑引用次数,还考虑每次引用的实际影响力。我们采用两种方法来证明新指数的效用。首先,我们使用一个作者群体的模拟模型,通过创建在固有发表习惯上彼此不同的各种“作者组”,以表明在三种不同情况下,网页排名指数比现有指数更公平:(i)当作者主要通过在低质量期刊上发表论文以自我引用其他论文来“操纵”他们的指数时;(ii)当作者进行大型团队合作以获得更多署名时;(iii)当作者将大部分时间用于产出真实但质量较低的出版物以操纵他们的指数时。其次,我们进行了两个实际案例研究:(i)谷歌学术定义的量子博弈论不断演变的作者群体;(ii)arXiv上高能物理(HEP)理论研究群体的一个快照。在这两个案例研究中,我们发现当使用h指数和网页排名指数进行比较时,顶级作者的名单差异非常显著。我们表明,在这两种情况下,进行大型团队合作和/或发表影响力较小论文的作者往往相对更受h指数青睐,而网页排名指数突出的是做出相对较少决定性贡献、撰写用于突出不同学科之间联系的论文或通常在较小团队中工作的作者。因此,我们认为与现有衡量方法相比,网页排名指数是一种本质上更公平、更细致入微的用于量化科学家发表记录的指标。