Visualization of co-readership patterns from an online reference management system
作者：
Highlights：
• We analyze the applicability of readership data for knowledge domain visualizations.
• 69.2% of articles in an avg. user library can be attributed to a single subject area.
• We create a visualization of educational technology based on co-readership patterns.
• 80% of the publications included are from within ten years of data collection.
• The characteristics of the readers introduce certain biases to the visualization.
摘要
Highlights•We analyze the applicability of readership data for knowledge domain visualizations.•69.2% of articles in an avg. user library can be attributed to a single subject area.•We create a visualization of educational technology based on co-readership patterns.•80% of the publications included are from within ten years of data collection.•The characteristics of the readers introduce certain biases to the visualization.
论文关键词：Relational scientometrics,Topical distribution,Knowledge domain visualization,Mapping,Altmetrics,Readership statistics
论文评审过程：Received 5 August 2014, Revised 3 December 2014, Accepted 8 December 2014, Available online 12 January 2015.
论文官网地址：https://doi.org/10.1016/j.joi.2014.12.003
