Analysing panel co-attendance in scientific conferences A new avenue to explore academic sociality #Sunbelt2020 virtual sessions on 𝘽𝙞𝙥𝙖𝙧𝙩𝙞𝙩𝙚 𝙉𝙚𝙩𝙬𝙤𝙧𝙠𝙨 & 𝙋𝙧𝙤𝙟𝙚𝙘𝙩𝙞𝙤𝙣𝙨 Empirical Insights from Bipartite and Multipartite Networks July 15, 2020 François Briatte · ESPOL, Catholic U. of Lille, France Marion Maisonobe · Géocités, CNRS, Paris, France
Background (network science + science studies) ● Research on scientific collaboration and networks mainly relies on co-authorship data ● Many other types of interactions contribute to the circulation of ideas between scholars and to the emergence of scientific groups ● Among them, social links derived from participation to conferences and panel co-attendance ● Interesting to explore, with conference programmes and lists of participants often openly accessible on the Web
● Panel co-attendance in two scientific conferences about green chemistry (ISGC) and political science (AFSP) ● Conference structure (sessions, topics, etc.) and its evolution can inform specialty/discipline dynamics ● Panel co-attendance used as a proxy for knowledge circulation between participants/places ● Common methodology applied to both conferences, through several conference years T (ISGC) = 6 years, T (AFSP) = 10 years (every odd year) Goals of the project
Comparable properties ● Both conferences count ~ 700–1,000 participants i, with most attending a single panel j ● Attending several years is frequent but not the modal behaviour (return rate ~ 25% for ISGC, ~ 30% for AFSP) ● ISGC (green chemistry, organised in La Rochelle) is much more internationalized (50–60%) than AFSP (French or Francophone political science, itinerant, max. 20% intl.) ● Yet both conferences attract participants from roughly the same number of countries (~ 60)
Each tie captures one panel co-attendance in the panel/participant bipartite graph. We used all ties > 1 (2+ panel co-attendance at the same conference) to extract the backbone of each graph. Universal method used, but perhaps edge distribution justifies another approach? Edge weight distributions of one-mode projections 1 tie 2 ties 3 ties 4 ties 5 ties ISGC 2015 17080 122 6 4 ISGC 2017 20444 230 26 4 2 ISGC 2019 18230 358 24 8 4 AFSP 2009 14478 230 8 AFSP 2011 9538 34 AFSP 2013 15364 100 2 AFSP 2015 17476 114 AFSP 2017 9934 52 AFSP 2019 15180 82
Next steps (suggestions welcome) ● Weighting scheme of the ( Participant i × Panel j ) bipartite adjacency matrix: 1/N i weights? ● Additional data on participants (e.g. affiliations, publications, dissertation committees) — ongoing work ● Characteristics (socio-demographic, geographic) of the nodes connected by the network backbone ● Temporal analysis with TERGMs? (institution-/city-level homophily sustained through conference years; cohorts) ● Additional data from similar conferences? see experimental takes at epsa2020 and statconf
● ISGC conference data shared by its managing company ● AFSP conference data scraped from the AFSP website see congres-afsp for the code and (preliminary) data ● Graph visualizations performed with igraph (Csárdi), ggraph (Pedersen) and graphlayouts (Schoch) ● Backbone extraction performed with backbone (Domagalski, Neal and Sagan) ● References for final report on Zotero Sources