Building a social media network map of artworld influencers
Constructing an Artworld Influencers Network by Mining Social Media
Social and Information NetworksComputation and LanguageComputers and Society
Summary
Identifying key people in the artworld can be tricky, especially when some don’t even have social media accounts. The authors show how starting with a small list of known art influencers on Twitter and analyzing their tweets can reveal new important actors in the art community. They group these actors into communities and measure how influential each is in the network. This approach gathers valuable data about the artworld that would otherwise be very hard to collect.
What this means in practice
- •For art marketing teams: Identify influential and emerging artworld figures to target for promotions and events using social media-based networks.
- •For social media analytics services: Enhance influencer discovery tools by integrating NLP and network analysis techniques to uncover offline important actors from online data.$Commercial implications: Enables creation of advanced influencer identification products sold to marketing agencies and brands interested in the art sector.
Authors
Amalia Foka
Abstract
The author shows a methodology for constructing a network map of the artworld. The tweets posted by a manually comprised set of exemplar artworld actors and Natural Language Processing (NLP) methods are used to identify significant artworld actors, including those that do not own a Twitter account. Identified artworld actors form communities detected with the Louvain method, and their authority is evaluated with the HITS centrality method. The resulting artworld network exhibits the ability, starting with a small set of exemplar actors, to identify new artworld actors and provides a wealth of data that would be very hard to collect otherwise.