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import graph_builder as gb
import matplotlib.pyplot as plt
def find_hubs_in_csv_network_files(n_hubs=20, num_files = None, file_name=None, plot_title=None):
Controller function for the analysis process. User provides a few settings
and this function will load the graph, setup all edges and nodes, define the
important hub nodes, and make a plot.
n_hubs: how many nodes to treat as special "important hubs"
num_files: how many of the CSV files to read, None defaults to read all
file_name: string, if provided, saves the network graph to file, otherwise shows the plot
plot_title: label for plot, if needed (string)
return: None
graph = gb.build_directed_graph_from_csvs("data/", num_files=num_files)
position, network, ax = gb.draw_di_graph(graph, title=plot_title)
hub_nodes = gb.get_hub_nodes(graph, top_n_hubs=n_hubs)
for user, connections in hub_nodes:
print("User {} has been retweeted {} times".format(user, connections))
gb.highlight_important_nodes(graph, position, hub_nodes=hub_nodes, top_n_hubs=n_hubs)
if type(file_name) == str:
plt.savefig(file_name, dpi=150)
if __name__ == "__main__":
find_hubs_in_csv_network_files(file_name="images/example_network_hubs.png", num_files=None,
plot_title="Conversation Drivers for topic 'Trump'")