<table><caption>Table B.5: Details of the citation-network clusters shown in Fig. 3: cluster number, number of papers in cluster, average year of publication, and cluster label.</caption><thead><tr><th>#</th><th>Papers</th><th>Avg. year</th><th>Label</th></tr></thead><tbody><tr><td>C0</td><td>13872</td><td>2015.5</td><td>Black-hole physics</td></tr><tr><td>C1</td><td>10043</td><td>2014.3</td><td>AGN, quasars, and galaxies</td></tr><tr><td>C2</td><td>6984</td><td>2016.2</td><td>Gravitational waves: binary BHs</td></tr><tr><td>C3</td><td>5574</td><td>2013.5</td><td>X-ray binaries, accretion disks</td></tr><tr><td>C4</td><td>5104</td><td>2014.4</td><td>High-redshift quasars, reionisation</td></tr><tr><td>C5</td><td>4846</td><td>2014.5</td><td>Jets, blazars</td></tr><tr><td>C6</td><td>4195</td><td>2013.9</td><td>Seyfert galaxies, emission lines</td></tr><tr><td>C7</td><td>2686</td><td>2013.9</td><td>Radio galaxies, clusters</td></tr><tr><td>C8</td><td>2613</td><td>2014.6</td><td>Galactic centre</td></tr><tr><td>C9</td><td>1566</td><td>2018.7</td><td>Primordial BHs, early universe</td></tr><tr><td>C10</td><td>1332</td><td>2015.7</td><td>Gravitational waves: SMBHs</td></tr><tr><td>C11</td><td>1186</td><td>2014.3</td><td>Gravitational lensing</td></tr><tr><td>C12</td><td>923</td><td>2018.0</td><td>TDEs, time domain</td></tr></tbody></table>

tion bias and error propagation in evidence-bases informing the evaluation of hypotheses (Greenberg, 2009; Leng, 2018).

To construct the citation network discussed in §2.1, we retrieved a large literature from the Web of Science (WoS) Core Collection by searching for the following terms in the title, abstract, and associated keywords of indexed papers in prominent astrophysics journals: TS = ("black hole" OR "black holes" OR "active galactic nucleus" OR "active galactic nuclei" OR "galaxies: nuclei" OR "quasar" OR "quasars").

This search query returned a total of 61,036 articles and reviews published between January 2003 and March 2024. All metadata associated with these were retrieved in March 2024. These data were restructured in the R statistical environment into a: 'Node-attribute list' that contains (i) a unique ID for each unique reference string; (ii) WoS unique identifier number; (iii) Digital Object Identifier (DOI), if available; (iv) name of all authors; (v) title of paper; (vi) journal of publication; (vii) year of publication; and (viii) total number of citations recorded by WoS). An 'edge list' was also built from the bibliographies of retrieved papers containing two columns: Source and Target, which record the unique identifiers of each citing and cited paper, respectively.

We restrict our analysis to the retrieved papers with full bibliographic data, and focused only on the main component; i.e., the largest connected network in which an undirected path of edges connects any two randomly chosen nodes together. This leaves a network containing 60,924 papers connected together by 1,378,057 citation links. To cluster this network, modularity maximisation (Newman and Girvan, 2004) via the Leiden algorithm (Traag et al., 2019) was performed in R using the 'igraph' package resulting in 13 clusters at $Q = 0.67$ (see Eqn B.1 below) with the following parameters: resolution 1, iterations 100, repetitions 100. Modularity maximization is a method used to identify communities within a network by optimizing the modularity value $Q$. It measures the strength of division of a network into clusters, with higher values indicating denser connections within clusters compared to between them. Due to

the directed acyclic structure of citation networks, we converted the network into an undirected variant following (Speidel et al., 2015). For an undirected graph, modularity is calculated by:

$$Q = \frac{1}{2m} \sum_{i,j} \left( A_{ij} - \frac{d_i d_j}{2m} \right) = \delta(c_i, c_j), \quad (B.1)$$

where $m$ is the total number of edges, $A_{ij}$ is set to 1 if there is an edge between nodes $i$ and $j$ or otherwise is set to 0, $\frac{d_i d_j}{2m}$ is the probability of an edge between two nodes proportional to their degree, the delta function ($\delta$) is set to 1 if $i$ and $j$ are in cluster $c$ or otherwise is set to 0.

We report the contingency matrices for the cluster network in Table B.6 which show the percentage of papers within-network citations (top) and within-network references (bottom) directed within and between clusters. For example, the diagonal lines indicate how “insular” a given sub field (i.e., research community) is in terms of citations (top section) and references (bottom section): C0 and C9 (“black-hole physics” and “primordial BHs and the early universe”) tend to reference (and are cited by) other studies within their cluster while C7 and C10 (“radio galaxies, clusters” and “Gravitational waves: SMBHs”) are much more open in their referencing and citations, although they are much smaller clusters than C0.

## References

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<table><caption>Proportion of within-network citations from within a given cluster and between clusters</caption><thead><tr><th></th><th>C0</th><th>C1</th><th>C2</th><th>C3</th><th>C4</th><th>C5</th><th>C6</th><th>C7</th><th>C8</th><th>C9</th><th>C10</th><th>C11</th><th>C12</th></tr></thead><tbody><tr><th>C0</th><td><strong>93.3%</strong></td><td>0.2%</td><td>4.9%</td><td>2.6%</td><td>0.4%</td><td>0.8%</td><td>0.8%</td><td>0.2%</td><td>7.4%</td><td>2.6%</td><td>1.2%</td><td>1.4%</td><td>0.5%</td></tr><tr><th>C1</th><td>0.1%</td><td><strong>77.3%</strong></td><td>0.7%</td><td>3.1%</td><td>9.9%</td><td>2.3%</td><td>13.4%</td><td>18.2%</td><td>4.5%</td><td>0.2%</td><td>7.8%</td><td>2.8%</td><td>2.1%</td></tr><tr><th>C2</th><td>3.2%</td><td>0.8%</td><td><strong>85.1%</strong></td><td>4.4%</td><td>1.3%</td><td>0.8%</td><td>0.4%</td><td>0.4%</td><td>5.8%</td><td>4.5%</td><td>8.2%</td><td>1.7%</td><td>5.9%</td></tr><tr><th>C3</th><td>0.6%</td><td>1.0%</td><td>1.9%</td><td><strong>75.1%</strong></td><td>0.6%</td><td>2.4%</td><td>4.7%</td><td>2.2%</td><td>4.2%</td><td>0.1%</td><td>1.6%</td><td>0.7%</td><td>2.2%</td></tr><tr><th>C4</th><td>0.1%</td><td>6.1%</td><td>1.0%</td><td>0.8%</td><td><strong>79.5%</strong></td><td>1.0%</td><td>3.8%</td><td>2.1%</td><td>1.0%</td><td>0.7%</td><td>2.4%</td><td>3.1%</td><td>0.6%</td></tr><tr><th>C5</th><td>0.2%</td><td>1.2%</td><td>0.3%</td><td>2.9%</td><td>0.8%</td><td><strong>83.1%</strong></td><td>3.7%</td><td>6.2%</td><td>2.7%</td><td>0.1%</td><td>2.0%</td><td>1.2%</td><td>1.2%</td></tr><tr><th>C6</th><td>0.2%</td><td>4.8%</td><td>0.2%</td><td>4.8%</td><td>2.9%</td><td>2.5%</td><td><strong>66.7%</strong></td><td>2.8%</td><td>0.8%</td><td>0.0%</td><td>2.2%</td><td>7.1%</td><td>3.7%</td></tr><tr><th>C7</th><td>0.0%</td><td>4.4%</td><td>0.1%</td><td>1.7%</td><td>1.2%</td><td>3.4%</td><td>1.5%</td><td><strong>65.4%</strong></td><td>0.7%</td><td>0.1%</td><td>1.5%</td><td>0.5%</td><td>0.6%</td></tr><tr><th>C8</th><td>1.2%</td><td>1.0%</td><td>1.4%</td><td>2.3%</td><td>0.5%</td><td>1.9%</td><td>0.4%</td><td>0.6%</td><td><strong>68.6%</strong></td><td>0.4%</td><td>2.4%</td><td>0.3%</td><td>2.5%</td></tr><tr><th>C9</th><td>0.8%</td><td>0.1%</td><td>1.8%</td><td>0.2%</td><td>0.7%</td><td>0.2%</td><td>0.0%</td><td>0.1%</td><td>0.6%</td><td><strong>90.1%</strong></td><td>2.4%</td><td>1.2%</td><td>0.1%</td></tr><tr><th>C10</th><td>0.1%</td><td>1.9%</td><td>1.8%</td><td>0.7%</td><td>1.0%</td><td>0.8%</td><td>1.5%</td><td>1.0%</td><td>1.7%</td><td>0.9%</td><td><strong>66.1%</strong></td><td>1.4%</td><td>1.5%</td></tr><tr><th>C11</th><td>0.1%</td><td>0.5%</td><td>0.2%</td><td>0.1%</td><td>0.9%</td><td>0.2%</td><td>1.5%</td><td>0.3%</td><td>0.1%</td><td>0.4%</td><td>0.3%</td><td><strong>78.6%</strong></td><td>0.1%</td></tr><tr><th>C12</th><td>0.1%</td><td>0.8%</td><td>0.8%</td><td>1.4%</td><td>0.2%</td><td>0.5%</td><td>1.6%</td><td>0.4%</td><td>1.9%</td><td>0.1%</td><td>1.9%</td><td>0.2%</td><td><strong>78.8%</strong></td></tr></tbody></table>

<table><caption>Proportion of within-network references from within a given cluster and between clusters</caption><thead><tr><th></th><th>C0</th><th>C1</th><th>C2</th><th>C3</th><th>C4</th><th>C5</th><th>C6</th><th>C7</th><th>C8</th><th>C9</th><th>C10</th><th>C11</th><th>C12</th></tr></thead><tbody><tr><th>C0</th><td><strong>88.8%</strong></td><td>0.3%</td><td>4.6%</td><td>1.6%</td><td>0.3%</td><td>0.4%</td><td>0.6%</td><td>0.1%</td><td>2.4%</td><td>0.5%</td><td>0.2%</td><td>0.1%</td><td>0.1%</td></tr><tr><th>C1</th><td>0.0%</td><td><strong>82.5%</strong></td><td>0.4%</td><td>1.2%</td><td>4.0%</td><td>0.6%</td><td>5.7%</td><td>3.4%</td><td>0.9%</td><td>0.0%</td><td>0.9%</td><td>0.2%</td><td>0.2%</td></tr><tr><th>C2</th><td>3.3%</td><td>1.5%</td><td><strong>84.6%</strong></td><td>3.0%</td><td>1.0%</td><td>0.4%</td><td>0.3%</td><td>0.1%</td><td>2.0%</td><td>0.9%</td><td>1.7%</td><td>0.2%</td><td>0.9%</td></tr><tr><th>C3</th><td>0.9%</td><td>3.2%</td><td>2.9%</td><td><strong>80.1%</strong></td><td>0.6%</td><td>2.0%</td><td>5.6%</td><td>1.2%</td><td>2.3%</td><td>0.0%</td><td>0.5%</td><td>0.1%</td><td>0.5%</td></tr><tr><th>C4</th><td>0.1%</td><td>15.1%</td><td>1.2%</td><td>0.7%</td><td><strong>75.7%</strong></td><td>0.7%</td><td>3.8%</td><td>0.9%</td><td>0.4%</td><td>0.2%</td><td>0.6%</td><td>0.4%</td><td>0.1%</td></tr><tr><th>C5</th><td>0.4%</td><td>4.1%</td><td>0.6%</td><td>3.6%</td><td>1.1%</td><td><strong>78.1%</strong></td><td>5.2%</td><td>3.9%</td><td>1.7%</td><td>0.0%</td><td>0.7%</td><td>0.2%</td><td>0.3%</td></tr><tr><th>C6</th><td>0.3%</td><td>13.3%</td><td>0.2%</td><td>4.6%</td><td>3.0%</td><td>1.8%</td><td><strong>72.6%</strong></td><td>1.4%</td><td>0.4%</td><td>0.0%</td><td>0.7%</td><td>1.1%</td><td>0.8%</td></tr><tr><th>C7</th><td>0.1%</td><td>23.1%</td><td>0.3%</td><td>3.0%</td><td>2.5%</td><td>4.8%</td><td>3.1%</td><td><strong>61.0%</strong></td><td>0.7%</td><td>0.0%</td><td>0.9%</td><td>0.1%</td><td>0.3%</td></tr><tr><th>C8</th><td>3.7%</td><td>5.7%</td><td>4.2%</td><td>4.7%</td><td>1.1%</td><td>3.0%</td><td>0.9%</td><td>0.7%</td><td><strong>72.9%</strong></td><td>0.3%</td><td>1.5%</td><td>0.1%</td><td>1.2%</td></tr><tr><th>C9</th><td>3.5%</td><td>0.9%</td><td>7.6%</td><td>0.6%</td><td>2.3%</td><td>0.4%</td><td>0.1%</td><td>0.1%</td><td>1.0%</td><td><strong>80.7%</strong></td><td>2.2%</td><td>0.5%</td><td>0.1%</td></tr><tr><th>C10</th><td>0.6%</td><td>15.8%</td><td>7.3%</td><td>2.0%</td><td>3.1%</td><td>1.7%</td><td>4.9%</td><td>1.5%</td><td>2.4%</td><td>0.7%</td><td><strong>58.4%</strong></td><td>0.6%</td><td>1.0%</td></tr><tr><th>C11</th><td>1.0%</td><td>7.7%</td><td>1.4%</td><td>0.8%</td><td>5.7%</td><td>1.0%</td><td>9.5%</td><td>0.8%</td><td>0.4%</td><td>0.7%</td><td>0.5%</td><td><strong>70.2%</strong></td><td>0.2%</td></tr><tr><th>C12</th><td>0.3%</td><td>8.5%</td><td>4.5%</td><td>5.0%</td><td>0.8%</td><td>1.5%</td><td>6.9%</td><td>0.7%</td><td>3.6%</td><td>0.1%</td><td>2.1%</td><td>0.1%</td><td><strong>65.9%</strong></td></tr></tbody></table>

<caption>Table B.6: Contingency table showing the degree of cross citation or cross referencing between clusters. The top section shows the percentage of the total within-network citations (in degree) contributed by papers within and between the clusters; the data is read in column format, as indicated. The bottom section shows the percentage of the total within-network references (out degree) directed within and between clusters; the data is read in row format, as indicated.</caption>
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