Network signatures of success: Emulating expert and crowd assessment in science, art, and technology
The success of scientific, artistic, and technological works is typically judged by human experts and the public. Recent empirical literature suggests that exceptionally creative works might have distinct patterns of citation. Given the recent availability of large citation and reference networks, we investigate how highly successful works differ from less successful ones in terms of a broad selection of centrality indices. Our experiments show that expert opinion is better emulated than popular judgment even with a single well-chosen index. Our findings further provide insights into otherwise implicit assumptions about indicators of success by evaluating the success of works based on the patterns of references that they receive.