gabriela

Analyze the following statements about the Agglomerative (Ravasz) and Divisive (Girvan–Newman) hierarchical clustering algorithms, and determine whether each statement is True (T) or False (F):  1) The Agglomerative algorithm starts by treating each node in the network as an individual community and repeatedly merges the most similar communities until a stopping condition is reached. This stopping condition occurs when the density inside each community becomes maximal. 2) The Divisive algorithm follows a top-down strategy: it initially treats the entire network as a single community and progressively splits the network into smaller communities. 3) The result of the Agglomerative algorithm can depend on the linkage criteria adopted, such as single, complete, or average linkage. 4) In the Girvan–Newman algorithm, communities are identified by iteratively removing links with high centrality, since these links are more likely to connect different communities. 5) In the Agglomerative hi...

 Observe the following heatmaps which represent the correlation matrices   e ij   of two different networks (1) and (2). The bars represent the probability of connection between nodes with degrees  k 1  and  k 2 . Notice that some areas are highlighted in the figures, i.e. (u), (v), (w), and (x). Analyze the following statements regarding those areas and network characteristics to further mark them as True or False: 1) In network (1), the highlighted area (u) refers to the connection between a hub and a low-degree node, while the area (v) refers to the connection between two hubs. 2) In network (2), the highlighted area (w) refers to the connection between two low-degree nodes, while the area (x) refers to the connection between two hubs. 3) Network (1) represents a disassortative network since the probability of connection is stronger in the secondary diagonal. 4) Network (2) represents an assortative network. Also, if we applied degree-preserving randomiz...