A uniform scale model for Impact Factors of Chinese and English journals based on expert experience and data fusion

摘要

Although existing studies have covered journal impact factor from many aspects, how to set up a uniform scale model for impact factors of Chinese and English journals is still a problem to be solved and receives more attention in recent years: since current methods such as data classification and statistical classification are too ambiguous, they tend to turn impact factors of ten-plus journals into one, usually leading to massive information loss during data conversion, thus they fail to provide scientific and rational evaluation findings. With journal impact factor being one of important indices for the quality of academic papers and academic levels, the adoption of an effective uniform scale system for Chinese and English journals' impact factors has become a hot spot both for literature research institutions and universities. The paper proposes a conversion model of impact factors based on expert experience and data fusion, which is established by taking into account of expert views towards academic journals in Chinese and English within a certain field as well as objective evaluations of impact factors from the journals.