Diagrams are often used in scholarly communication. We analyse a corpus of diagrams found in scholarly computational linguistics conference proceedings (ACL 2017), and find inclusion of a system diagram to be correlated with higher numbers of citations after 3 years. Inclusion of over three diagrams in this 8-page limit conference was found to correlate with a lower citation count. Focusing on neural network system diagrams, we find a correlation between highly cited papers and "good diagramming practice" quantified by level of compliance with a set of diagramming guidelines. Two diagram classification types (one visually based, one mental model based) were not found to correlate with number of citations, but enabled quantification of heterogeneity in those dimensions. Exploring scholarly paper-writing guides, we find diagrams to be a neglected media. This study suggests that diagrams may be a useful source of quality data for predicting citations, and that "graphicacy" is a key skill for scholars with insufficient support at present.
翻译:在学术交流中经常使用图表。 我们分析了一系列在学术计算语言会议议事录(ACL 2017)中发现的图表,发现在三年后将系统图表与引用次数增加相关联。 在这次8页限制会议中将三个以上的图表与较低引用数相关联。 聚焦于神经网络系统图表,我们发现大量引用的论文和“良好图表做法”之间有相关关系, 符合一套图表指南的水平。 两种图表分类类型(一个以视觉为基础,一个以精神模型为基础)与引用数没有关联, 但能够量化这些层面的异质性。 探索学术性纸面编写指南, 我们发现图表是一个被忽视的媒介。 这项研究表明,图表可能是预测引用的有用质量数据来源, 而“ 特征” 是目前支持不足的学者的关键技能。