Community Identity in Astrophysics

Communities of the Dark Matter citation network [Duffee, 2018, p97] visualised with Gephi's Force Atlas algorithm, showing the overlap of the citation communities. This network consisted of 47 187 nodes and 161 870 links created from citations to and by 2659 papers on the subject of Dark Matter or MOND (MOdified Newtonian Dynamics, an alternative theory to Dark Matter), lodged in arXiv between 1992 and 2009.<br><br>The nodes are coloured according to the largest seven communities found by the Louvain algorithm with, in decreasing order of size:<br><b>- purple</b> traditional astrophysics (11.57%),<br><b>- green</b> high-energy physics (11.11%),<br><b>- blue</b> cosmology and gravitational lensing (10.92%),<br><b>- red</b> Dark Energy and alternate theories (10.45%),<br><b>- black</b> detection of particles and high-energy physics (8.15%),<br><b>- orange</b> Dark Matter models and galaxy clusters (8.15%),<br><b>- turquoise</b> MOND, an alternate theory to Dark Matter (7.53%)<br><br>Network statistics:<br><b>modularity</b> 0.617<br><b>average degree</b> 3.43<br><b>average clustering co-efficient</b> 0.067<br><br>The top seven communities were labelled by examining the titles of the papers in the community and the label was chosen to best represent the character of the majority of the titles. The layout is determined by the citations between papers and it is intuitive to find related areas adjacent to each other, particle physics next to high-energy physics and cosmology close to astrophysics. This layout places high-energy physics between particle physics and astrophysics,<br>a good location for theoretical work connecting astronomical observation with laboratory experiment. It also places MOND, one of several alternative theories, as overlapping<br>traditional astrophysics and Dark Energy + alternative theories. The separation of galaxy clusters and Dark Matter models from astrophysics could be due to a strongly self-contained research community but would need more investigation to verify that claim.<br><br><b>References</b>:<br><br>Duffee, Boyd (2018) 'Quantifying textual similarities across scientific research communities' Doctoral thesis, Keele University.<br><br>