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maximum-spanning-arborescence

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chirindaopensource / constructing_and_comparing_sentiment_spillover_networks

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End-to-End Python replication of Wu et al.'s (2026) Sentiment Networks methodology. Quantifies directed sentiment contagion across 34 tech equities via Transfer Entropy, Markov bootstrap significance filtering, weighted PageRank centrality, and Chu-Liu/Edmonds Maximum Spanning Arborescence. Compares News vs. Social Media information topologies.

python time-series sentiment-analysis network-topology information-theory markov-chain pagerank networkx graph-theory quantitative-finance network-analysis causal-inference transfer-entropy information-flow shannon-entropy high-frequency-data behavioral-finance rolling-window spillover-effects maximum-spanning-arborescence
  • Updated May 9, 2026
  • Jupyter Notebook

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