【目的】 从多维度、多指标融合的信息计量视角来综合评价学术期刊影响力,为学术期刊影响力评价提供新的方法与思路。【方法】 以国际图书情报学期刊为例,从学术影响力(FAI)、社会影响力(FSI)和共被引网络影响力(FCO)3个维度选取指标来构建学术期刊影响力评价模型。对指标数据进行归一化处理,使用相关性分析、社会网络分析、因子分析、二维坐标四象限、三维空间坐标映射等方法对3个维度评价和样本期刊级别进行划分。【结果】 8个传统引文指标间呈高度正相关,10个Altmetrics 指标间呈不同程度正相关,且2个维度的指标在整体上与内部间都具有较显著的一致性。共被引网络中节点的3种中心性指标均呈不同程度的正相关。共被引期刊影响力可分为主导、跨子群、快速依附和子群内共被引4种类型。FAI与FSI、FCO呈较强正相关,但FSI与FCO呈低度正相关。【结论】 FAI与FCO对FSI具有较好补充作用,但3种评价维度仍存在一定差异,并不可完全替代。
[Purposes] This paper aims to comprehensively evaluate the academic journals influence from the perspective of multi-dimensional and multi-indicator fusing informetrics, and provide new methods and ideas for the evaluation of academic journal influence. [Methods] Taking international LIS journals as examples, this paper constructed an evaluation model of academic journal influence by using multi-indicator fusion method and selecting indicators from three dimensions: academic influence(FAI), social influence(FSI), and co-citation network influence(FCO). Through normalized processing, three dimensions were evaluated and sample journal types were classified by correlation analysis, social network analysis, factor analysis, two-dimensional coordinate four quadrant, and three-dimensional space coordinate system. [Findings] There are high positive correlations between the 8 traditional citation indicators, and different degree of positive correlations among the 10 Altmetrics indicators, and the indicators in two dimensions are significantly consistent with each other on the whole and internally. Three kinds of centrality indicators of the nodes in co-citation network are all correlated with each other. Meanwhile, it is found that there are four node influence types: dominant, cross-subgroup, fast-attached, and within the subgroup co-cited. FAI has a strong positive correlation with FSI and FCO, while FCO has a low positive correlation with FSI. [Conclusions] FAI and FCO are complementary to FSI, however, the three evaluation dimensions are still different and cannot be completely replaced.
Evaluation of academic journal,
Co-citation network indicators,
Co-citation network influence