Package: cidre
Python package for the CItation-Donor-REcipient (CIDRE) algorithm.CIDRE is an algorithm to find anomalous groups in directed and weighted networks.
An anomalous group consists of donor and recipient nodes, connected by edges with excessive edge weights (i.e., excessive edges).
A donor is a node providing excessive edges to other member nodes.
A recipient is a node having excessive edges from other member nodes.If you use this package, please cite:@misc{kojaku2021cartel,
      title={Detecting citation cartels in journal networks},
      author={Sadamori Kojaku and Giacomo Livan and Naoki Masuda},
      year={2021},
      eprint={2009.09097},
      archivePrefix={arXiv},
      primaryClass={physics.soc-ph}}RequirementsPython 3.7 or laterInstallpip install cidreExamplesToy network with communitiesCitation network of journals in 2013A minimal exampleimportcidrealg=cidre.Cidre(group_membership)groups=alg.detect(A,threshold=0.15)group_membership(Optional): If the network has communities, and the communities are not anomalous, tell the communities to CIDRE with this argument.group_membershipshould be numpy.array or list with element,group_membership[i], indicating the group to which node i belongs. Otherwise, setgroup_membership=None.A: Adjacency matrix of the input network (can be weighted or directed). Should be either an nx.Graph or scipy.sparse_csr_matrix. In case of scipy.sparse_csr_matrix format, A[i,j] indicates the weight of the edge from node i to j.threshold: Threshold for the donor and recipient nodes. A larger threshold will yield tighter and smaller groups.groups: List ofGroupinstances. SeeGroup classsection.Group classGroupis a dedicated class for groups of donor and recipient nodes.The donor and recipient nodes of a group, denoted bygroup, can be obtained bygroup.donors# {node_id: donor_score}group.recipients# {node_id: recipient_score}group.donorsis a dict object taking keys and values corresponding to the node IDs and the donor scores, respectively.group.recipientsis the analogous dict object for the recipient nodes.The number of nodes and edges within the group can be obtained bygroup.size()# Number of nodesgroup.get_within_edges()# Number of edges within this groupVisualizationcidrepackage provides an API to visualize small groups. Before using this API, set up your canvas byimportmatplotlib.pyplotaspltwidth,height=7,10fig,ax=plt.subplots((width,height))Then, passaxtogether withgroupthat you want to visualize toDrawGroupclass:importcidredc=cidre.DrawGroup()dc.draw(group,ax=ax)This will show a plot like this:The left and right nodes correspond to the donor and recipients nodes, respectively.The color of each edge corresponds to the color of the source node (i.e., the node from which the edge emanates).The width of each edge is proportional to the weight of the edge.The text next to each node corresponds to the ID of the node, or equivalently the row id of the adjacency matrixA.Instead of node IDs, you may want to display the nodes' labels. To do this, prepare a dict object taking IDs and labels as keys and values, respectively, e.g.,node_labels={0:"name 1",1:"name 2"}Then, pass it to thedrawfunction asnode_labelsargument, i.e.,dc.draw(group,node_labels=node_labels,ax=ax)