Graph Module

The graph module provides functionality for building, exporting, and managing concept network graphs.

Functions

build_graph

Build a NetworkX graph from a list of concepts.

Graph Types:

chain: Connect consecutive concepts (recommended for narrative flow)
dense: Connect all concepts to each other

Example:

from wosecopy import build_graph

concepts = ['belief', 'faith', 'church', 'prayer']

# Chain graph (narrative flow)
chain_graph = build_graph(concepts, graph_type='chain')

# Dense graph (all connections)
dense_graph = build_graph(concepts, graph_type='dense')

build_graphs_from_list

Build multiple graphs from a list of concept lists.

Example:

from wosecopy import build_graphs_from_list

concept_lists = [
    ['a', 'b', 'c'],
    ['x', 'y', 'z']
]
graphs = build_graphs_from_list(concept_lists)

export_graph

Export a single graph to a file.

Supported Formats:

graphml: GraphML format (recommended for Gephi, Cytoscape)
gexf: GEXF format
gml: Graph Modelling Language
edgelist: Simple edge list

Example:

from wosecopy import build_graph, export_graph

graph = build_graph(['a', 'b', 'c'])
export_graph(graph, 'my_graph.graphml', format='graphml')

export_graphs

Export multiple graphs to a directory.

Example:

from wosecopy import export_graphs

graphs = [graph1, graph2, graph3]
export_graphs(graphs, 'graphs/', prefix='story', format='graphml')
# Creates: graphs/story_0.graphml, graphs/story_1.graphml, etc.

load_graph

Load a graph from a file.

Example:

from wosecopy import load_graph

graph = load_graph('my_graph.graphml', format='graphml')

merge_graphs

Merge multiple graphs into a single graph.

Example:

from wosecopy import merge_graphs

merged = merge_graphs([graph1, graph2, graph3])

get_graph_summary

Get basic statistics about a graph.

Returns:

num_nodes: Number of nodes
num_edges: Number of edges
is_connected: Whether graph is fully connected
num_components: Number of connected components
density: Graph density (0-1)

Example:

from wosecopy import build_graph, get_graph_summary

graph = build_graph(['a', 'b', 'c'], graph_type='chain')
summary = get_graph_summary(graph)
print(summary)
# {'num_nodes': 3, 'num_edges': 2, 'is_connected': True, ...}

Usage Examples

Complete Workflow

from wosecopy import wosecopyExtractor, build_graphs_from_list, export_graphs
import pandas as pd

# Extract concepts
extractor = wosecopyExtractor(language='en')
df = pd.read_csv('stories.csv')
concepts = extractor.get_wosecopy(df)

# Build graphs
graphs = build_graphs_from_list(concepts, graph_type='chain')

# Export for Gephi
export_graphs(graphs, 'graphs/', format='graphml')

Analyzing Individual Graphs

from wosecopy import build_graph, get_graph_summary

concepts = ['belief', 'faith', 'church', 'prayer', 'community']
graph = build_graph(concepts)

# Get summary
summary = get_graph_summary(graph)
print(f"Nodes: {summary['num_nodes']}")
print(f"Edges: {summary['num_edges']}")
print(f"Connected: {summary['is_connected']}")