Who Wants To Read This?: A Method For Measuring Topical Representativeness In User Generated Content Systems

This methods paper details an approach for identifying the representativeness of content in a user generated content (UGC) system while also accounting for endogeneity bias. We leverage metadata from an independent content provider to generate sets of commercially viable terms presumed to be of interest to specific audiences linking those terms to UGC. We describe our method and heuristics at a level of detail allowing others to follow or modify it to study both content representativeness and content gaps in UGC systems. We illustrate the method by investigating how well the English language Wikipedia addresses the content interests of four sample audiences: readers of men's and women's periodicals, and readers of political periodicals geared toward either liberal or conservative ideologies. We also share preliminary findings from each case study to demonstrate our method.