DISCUSSION OF "COAUTHORSHIP AND CITATION NETWORKS FOR STATISTICIANS"

作者：Kolar Mladen^*; Taddy Matt

来源：Annals of Applied Statistics, 2016, 10(4): 1835-1841.

DOI：10.1214/16-AOAS896D

• Networks
• spectral clustering
• text analysis
• eigengap

Pengsheng Ji and Jiashun Jin have collected and analyzed a fun and fascinating data set that we are eager to use as an example in a course on Statistical Network Analysis. In this comment, we partition the core of the paper citation graph and interpret the clusters by analyzing the paper abstracts using bag-of-words. Under the Stochastic Block Model (SBM), the eigengap reveals the number of clusters. We find several eigengaps and that there are still clusters beyond the largest eigengap. Through this illustration, we argue against a simplistic interpretation of model selection results from the Stochastic Block Model (SBM) literature. In short, don't mind the gap.

• 出版日期2016-12
• 单位Microsoft