network-science graph-theory heuristics network-analysis sis-model voter-model btc-alpha behavior-spread bilingual-model

Study and analyze the BTC-Alpha network to identify influence of trust behavior dynamics on bitcoin-based cryptocurrency. Also, analyze how the roles of important individuals with the network contribute to the dynamics of cryptocurrency networks, particularly with regard to the privacy and network security.

A. Dataset Information

• This is who-trusts-whom network of people who trade using Bitcoin on a platform called Bitcoin OTC. Since Bitcoin users are anonymous, there is a need to maintain a record of users’ reputation to prevent transactions with fraudulent and risky users. Members of Bitcoin OTC rate other members in a scale of -10 (total distrust) to +10 (total trust) in steps of 1. This is the first explicit weighted signed directed network available for research.

• Dataset Statistics:

Properties	Information
Nodes	5,881
Edges	35,592
Range of edge weight	-10 to +10
Percentage of positive edges	89%

• Source (Citation): The following BibTeX citation can be used:
  
  

@inproceedings{kumar2016edge,
  title={Edge weight prediction in weighted signed networks},
  author={Kumar, Srijan and Spezzano, Francesca and Subrahmanian, VS and Faloutsos, Christos},
  booktitle={Data Mining (ICDM), 2016 IEEE 16th International Conference on},
  pages={221--230},
  year={2016},
  organization={IEEE}
}

@inproceedings{kumar2018rev2,
  title={Rev2: Fraudulent user prediction in rating platforms},
  author={Kumar, Srijan and Hooi, Bryan and Makhija, Disha and Kumar, Mohit and Faloutsos, Christos and Subrahmanian, VS},
  booktitle={Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining},
  pages={333--341},
  year={2018},
  organization={ACM}
}

• Files:

File	Description
soc-sign-bitcoinotc.csv.gz	Weighted Signed Directed Bitcoin OTC web of trust network

• Data Format: Each line has one rating, sorted by time, with the following format:
  
  SOURCE, TARGET, RATING, TIME
  where
  • SOURCE: node id of source, i.e., rater
  • TARGET: node id of target, i.e., ratee
  • RATING: the source’s rating for the target, ranging from -10 to +10 in steps of 1
  • TIME: the time of the rating, measured as seconds since Epoch.

B. Dataset Acquisition

• To acquire the Bitcoin Alpha Trust Weighted Signed Network in its present form we need to the following minor edition:
• Class: The class of each trader (node).
  • Trusty Class (𝒯): +1
  • Normal Class (𝒩): 0
  • Suspecious Class (𝒮): -1
• The class label of the node v is calculated as following -
  
  
  where
  • $deg^{w^-}(v)$ : Weighted in-degree of node v.
  • $L$ : Number of edges in network.
  • $N$ : Number of nodes in network.
  • $\left < w \right >$ : Average weight of the network.

C. Network Visualization

• Orange nodes represent trusty (𝒯) class.
  • 𝟑𝟔.𝟒𝟖 % of the network
• Sky-blue nodes represent normal (𝒩) class.
  • 𝟓𝟒.𝟗𝟔 % of the network
• Black nodes represent suspicious (𝒮) class.
  • 𝟖.𝟓𝟔 % of the network
• Edges acquired the source nodes color.

D. Published Article

• To access the published article click here.
• To cite the published article use following:

  @article{islam2024itrustbd,
  title={iTrustBD: Study and Analysis of Bitcoin Networks to Identify the Influence of Trust Behavior Dynamics},
  author={Islam, Md Jahidul and Islam, Md Rakibul and Basar, Md Abul},
  journal={SN Computer Science},
  volume={5},
  number={5},
  pages={476},
  year={2024},
  publisher={Springer}
  }