ciga 0.0.2

Character interaction temporal graph analysis

license

CIGA: Character Interaction Graph Analyzer

CharNet is a Python package designed for performing graph analysis on dynamic social networks based on narratives. It is a reimplementation of CharNet using igraph.

• Github: https://github.com/MediaCompLab/CIGA

Simple example

---

import ciga as cg
import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('bigbang_lines_test.csv')


def weight_func(interaction):
    return 1


interactions = cg.prepare_data(df, ('Season', 'Episode', 'Scene', 'Line'),
                               source='Speaker', target='Listener', interaction='Words')
sub_interactions = cg.segment(interactions, start=(1, 1, 1, 1), end=(2, 1, 1, 1))

weights = cg.calculate_weights(sub_interactions, weight_func)
agg_weights = cg.agg_weights(weights, ('Season', 'Episode', 'Scene', 'Line'), agg_func=lambda x: sum(x))

tg = cg.TGraph(data=agg_weights, position=('Season', 'Episode', 'Scene', 'Line'), directed=False)

graph = tg.get_graph()
fig, ax = plt.subplots()
cg.iplot(graph, target=ax)

res = cg.tgraph_degree(tg, weighted=True, normalized=True)

res.to_csv('results.csv')

plt.show()

Install

---

Install the latest version of CharNet:

$ pip install ciga

Install with all optional dependencies:

$ pip install ciga[all]

To Do

• Add non-directed graph support
• Add closeness centrality
• Add Eigenvector centrality
• Add Louvain community detection
• Add temporal visualization
• Add centrality visualizer (with visualization)

License

Released under the GNU General Public License v3.0.

Copyright (c) 2024 Media Comprehension Lab