Constructing an Artworld Influencer Network by Mining Social Media

Abstract The author demonstrates a methodology for constructing a network map of the artworld. She uses tweets posted by a manually composed set of exemplar artworld actors and Natural Language Processing (NLP) methods to identify significant artworld actors, including those without Twitter accounts. Identified artworld actors form communities detected using the Louvain method, and their authority is evaluated with the HITS centrality method. The resulting artworld network exhibits the ability to proceed from a small original set of exemplar actors to identify new artworld actors and provides a wealth of data that would be difficult to collect otherwise.