Automatic classification of citation function by new linguistic features
Rui Meng, Wei Ping Lu, Yu Chi, Shuguang Han · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · 2017
Citation function presents the functional role of a reference in its citing article. These functional information enrich the citation analysis in a semantic perspective and can be used for improving the applications of citation analysis. Though many works on automatic classification have been done, the performance of existing studies cannot satisfy the requirement of analysis on large-scale academic data. In order to overcome the performance bottleneck, in this poster we present some useful features by analyzing and finding unique linguistic patterns in citation context. Our experiments on existing dataset shows the effectiveness of these new features with Support Vector Machine. The performance reaches 86.54% accuracy and a macro F-score of 0.795, which gains an improvement over 20% than previous study on the same dataset.