This dataset consists of 504 reports, speeches, and official press releases related to the jihadi conflict in Burkina Faso and Niger, collected from online sources between mid-January 2024 and March 2024. The data includes 343 documents from governments and the military, as well as 161 documents from non-governmental organizations (NGOs) and international non-governmental organizations (INGOs) operating in the two countries.The documents were selected based on their relevance to the jihadi conflict, either directly describing or commenting on the conflict or discussing the authors' actions or attitudes towards it. The dataset covers the period from 2020 to 2023, which was a critical period for both countries due to significant political events, such as the creation of the Volontaires pour la défense de la Patrie (VDP) militia in Burkina Faso in 2020 and the election of President Mohamed Bazoum in Niger.The dataset is available in various formats, including digitalized documents (scanned PDF or image versions of physical documents), and is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. Researchers can access and use the data for non-commercial purposes, provided they give appropriate credit to the original creators.This dataset provides a comprehensive collection of primary sources related to the jihadi conflict in Burkina Faso and Niger, offering valuable insights into the perspectives and actions of governments, the military, NGOs, and INGOs during a critical period in the conflict's history.

Datasets provided in this storage are introduced in the paper: MiNT: Multi-Network Training forTransfer Learning on Temporal Graphs

• Each .csv file represents all transactions of the token network that has the same name as the file name (
• Each transaction corresponds to a row in each file.
• Each transaction has:
  • blockNumber : is the block ID of Ethereum that includes this transaction
  • timestamp: time that the transaction is made in UNIX timestamp format
  • tokenAddress : the address that specifies a unique ERC20 token
  • from: address of sender
  • to: address of receiver
  • value: the amount the transaction
  • fileBlock: we split the whole number of blocks count to 35 buckets and assigned the bucket ID to the transaction to trace the blocks
• To use the same setting as described in the papers, we include edge list and label that contain node interactions and labels for each snapshot in each token network.
  • Each transaction in the edge list also has "from","to" and "amount" fields, but with an additional "snapshot" field to indicate the index of the snapshot that the transaction below to
  • Each row in label file indicates the ground truth label of the snapshot having an index corresponding to the index of the row (e.g first row indicates the label of the first snapshot)
  • We provided the way to generate edge lists and label files in the following Github repository: https://github.com/benjaminnNgo/ScalingTGNs/blob/main/script/utils/TGS.py
• However, we also provide raw .csv to divide into generate edgeslist and label with a different setting.
• There are two set of labels for two different tasks, MiNT_labels_Edge_GS is for Edge Growth or Shrink and MiNT_labels_LargeConComp_GS is for Largest Connect Component Growth or Shrink task