Table 5 Descriptive statistics of derived MVMC clusters. Centralities are calculated on the cluster by cluster networks per time period
From: Mapping state-sponsored information operations with multi-view modularity clustering
Era | Cluster | Size | Centrality (Total) | Centrality (Betweenness) |
|---|---|---|---|---|
1 | Cluster 0: Defend Hong Kong | 3397 | 0.094 | 0.000 |
Cluster 1: Guo Wengui and Bannon | 2889 | 0.091 | 0.000 | |
Cluster 2: Hong Kong and Taiwan Elections | 659 | 0.016 | 0.153 | |
Cluster 3: Kpop Fans and Health Tips | 462 | 0.039 | 0.167 | |
Cluster 4: Stop Violence and Love Country | 367 | 0.005 | 0.000 | |
Cluster 5: Guo Liar and COVID-19 | 313 | 0.008 | 0.000 | |
Cluster 6: Love Hong Kong and Support the Police | 170 | 0.003 | 0.236 | |
2 | Cluster 0: Stop Violence and the Color Revolution | 5945 | 0.060 | 0.083 |
Cluster 1: Guo Wengui Con Man | 5534 | 0.057 | 0.276 | |
Cluster 2: Encouraging China during COVID | 2746 | 0.031 | 0.032 | |
Cluster 3: Carrie Lam and Hong Kong Peace | 534 | 0.008 | 0.000 | |
Cluster 4: Stop Violence during Elections | 433 | 0.005 | 0.192 | |
Cluster 5: Punishment for Protestors | 369 | 0.004 | 0.058 | |
Cluster 6: Guo Wengui Fugitive | 338 | 0.004 | 0.208 | |
Cluster 7: Western Musicals and the Pandemic | 331 | 0.014 | 0.052 | |
Cluster 8: Assorted Entertainment and Hong Kong Encouragement | 314 | 0.007 | 0.038 | |
Cluster 9: Justin Bieber and Stopping Hong Kong Violence | 83 | 0.001 | 0.244 | |
Cluster 10: Hong Kong (Isolated) | 38 | 0.000 | 0.321 | |
Cluster 11: Guo Wengui (Isolated) | 15 | 0.000 | 0.173 |