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README.md

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 # email-Enron
 
-Some basic statistics of this dataset are:
-
-- Number of nodes 143
-- Number of hyperedges 1,512
-- Number of connected components 1
-
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+email-Enron is an undirected hypergraph built from the Enron email corpus, designed for higher-order network / hypergraph machine learning. In email communication, a single message can involve more than two people; this dataset captures that group interaction by modeling each email as a hyperedge connecting the sender and all recipients, while nodes represent Enron email addresses (restricted to a core set of employees).
+
+The hypergraph is stored in HIF (Hypergraph Interchange Format) as a JSON object, following the schema used to exchange higher-order network data across tools. Concretely, the dataset provides the canonical HIF fields—network-type, metadata, nodes, edges, and incidences—so you can reconstruct the full incidence structure without additional processing.
+
+In addition to the raw hypergraph topology, vector features are provided for both nodes and hyperedges (in their attribute dictionaries), enabling out-of-the-box experimentation with representation learning and downstream tasks:
+
+Spectral features: eigenvectors of the (hypergraph) Laplacian (computed via sparse eigensolvers).
+
+Node2Vec embeddings: random-walk–based structural embeddings.
+
+VilLain embeddings: self-supervised hypergraph representation learning via virtual label propagation.
+
+Basic statistics (as packaged here): 143 nodes, 1,512 hyperedges, 1 connected component.
+
 ```
 @article{Benson-2018-simplicial,
  author = {Benson, Austin R. and Abebe, Rediet and Schaub, Michael T. and Jadbabaie, Ali and Kleinberg, Jon},