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Twitter Neighbours dataset

This repository contains the dataset assembled as part of a APPRAISE project (H2020-SU-SEC-2020H2020-SU-SEC-2020)

Description

The dataset contains a sampled graph, extracted from Twitter, starting from a list of seed users. Each user is initially represented by a semantic embedding (vector) computed as the average text embedding of a sample of its tweets, while users are connected with each other through the 'following/follower' property on Twitter.

Statistics

  • number of users: 36122
  • number of edges: 84026
  • user initial embeddings size: 768

Files:

graph_train_and_test.pygeodata: is a compact representation of the graph for PyG usage.

twitter_neighs_graph.json: a dictionary containing:

  • 'adj_sparse': adjacency matrix in sparse representation
  • 'user_init_embs': initial user embedding, computed as average of text embedding of user tweets
  • 'train_test_split': 0/1 1D list, where 0 represents the user is in teh training set and 1 the user is in the test set