This is the accompanying webpage for the paper titled "Social Media Mining for the Analysis of the Art World" that will be presented in the Art and Artificial Intelligence Session of the 107th CAA Annual Conference.
In this paper a methodology for constructing a network that maps the structure of the artworld is proposed. It is based on mining Twitter in an attempt to identify the artworld actors (artists, museums, galleries, curators, etc.) as they exist online and discover connections amongst them. The ability to obtain a map the artworld from social media data is regarded as the first essential step for further exploring how Artificial Intelligence techniques can elaborate on the understanding of the artworld.
The different artworld networks constructed with our proposed methodology are shown below as interactive graphs so that they can be explored in more detail.
This network is contructed considering the interactions (mentions, retweets, friends) occurring amongst only the exemplar accounts.
This network is contructed considering all exemplars' interactions (mentions, retweets, friends). Exploring how exemplar actors of the artworld interact with others it enables the identification of new actors of the artworld, not included in the initial manually compiled list of exemplars.
This network is contructed considering exemplars' interactions only for the tweets that refer to an art-related events.
This network is contructed considering exemplars' interactions only for the tweets that refer to an art-related event that also include recognized named entities.