[Purpose/significance] We study the combinational novelty of academic papers' contents, providing a new perspective for research in academic impact.[Method/process] We apply text mining methods for extracting key-terms in the title, abstract and keywords part of all papers in a particular research field, and design three indicators-novel, medium and conventional combination rates for each paper by constructing a key-term co-occurrence network. Then we divide all papers into different novelty/convention combination types, and analyze the proportion of highly cited papers for different combination types.[Result/conclusion] We find that papers of high novelty and high conventionality have a significantly higher probability of becoming highly cited papers than other types of papers. The results imply that researchers should seek appropriate combination of novel and conventional knowledge in the process of scientific research.
Ren Haiying
,
Wang Deying
,
Wang Feifei
. Relationship Between Novelty of Key-Term Combinations and Papers' Scientific Impact[J]. Library and Information Service, 2017
, 61(9)
: 87
-93
.
DOI: 10.13266/j.issn.0252-3116.2017.09.011
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