Bornmann Lutz, Haunschild Robin, Hug Sven E
1Division for Science and Innovation Studies, Administrative Headquarters of the Max Planck Society, Hofgartenstr. 8, 80539 Munich, Germany.
2Max Planck Institute for Solid State Research, Heisenbergstr. 1, 70569 Stuttgart, Germany.
Scientometrics. 2018;114(2):427-437. doi: 10.1007/s11192-017-2591-8. Epub 2017 Dec 2.
During Eugene Garfield's (EG's) lengthy career as information scientist, he published about 1500 papers. In this study, we use the impressive oeuvre of EG to introduce a new type of bibliometric networks: keyword co-occurrences networks based on the context of citations, which are referenced in a certain paper set (here: the papers published by EG). The citation context is defined by the words which are located around a specific citation. We retrieved the citation context from Microsoft Academic. To interpret and compare the results of the new network type, we generated two further networks: co-occurrence networks which are based on title and abstract keywords from (1) EG's papers and (2) the papers citing EG's publications. The comparison of the three networks suggests that papers of EG and citation contexts of papers citing EG are semantically more closely related to each other than to titles and abstracts of papers citing EG. This result accords with the use of citations in research evaluation that is based on the premise that citations reflect the cognitive influence of the cited on the citing publication.
尤金·加菲尔德（EG）作为信息科学家有着漫长的职业生涯，他发表了约1500篇论文。在本研究中，我们利用EG令人印象深刻的全部作品引入一种新型的文献计量网络：基于引文上下文的关键词共现网络，这些引文在某一论文集中被引用（此处：EG发表的论文）。引文上下文由特定引文周围的词汇定义。我们从微软学术搜索中检索了引文上下文。为了解释和比较这种新型网络的结果，我们还生成了另外两个网络：基于（1）EG的论文以及（2）引用EG出版物的论文的标题和摘要关键词的共现网络。这三个网络的比较表明，EG的论文与引用EG论文的引文上下文在语义上彼此之间的关联比与引用EG论文的标题和摘要的关联更为紧密。这一结果与研究评估中对引文的使用相一致，其前提是引文反映了被引文献对引用文献的认知影响。
