We are developing algorithms and techniques for identifying and analyzing patterns in blockchain transactions
We are among the first publishers of scientific peer-reviewed papers related to the analysis of blockchain transactions using methods already validated for social media nodes interaction. By applying these methods, we aim to gain insights into the patterns and behaviours of participants in the blockchain, which could have important implications for improving the security and efficiency of the blockchain, or for identifying trends and patterns that could be used for predictive analytics.
Research and Publications
- Developing algorithms and techniques for identifying and analyzing patterns in blockchain transactions
- Investigating the factors that influence the behavior of participants in the blockchain
- Identifying trends and patterns that could be used for predictive analytics
Our research is ongoing, and we are always looking for ways to improve and expand upon our findings. We believe that by collaborating with other researchers and experts in the field, we can make significant contributions to the understanding of blockchain technology and its potential applications.
Peer Reviewed Scientific Papers
- S. Casale-Brunet, L. Chiariglione, M. Mattavelli, “Exploring the data of blockchain-based metaverses,” In Proceedings of the IEEE International Conference on Metaverse Computing, Networking and Applications (IEEE METACOM 2023), June 26–28, 2023, Japan
- S. Casale-Brunet, P. Ribeca, P. Doyle and M. Mattavelli, “Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem,” In Proceedings of the 2021 IEEE International Conference on Blockchain (Blockchain), 2021, pp. 188-195, doi: 10.1109/Blockchain53845.2021.00033.
- S. Casale-Brunet, M. Zichichi, L. Hutchinson, M. Mattavelli, and S. Ferretti, “The impact of NFT profile pictures within social network communities,” In Proceedings of the 2022 ACM Conference on Information Technology for Social Good (GoodIT ’22). Association for Computing Machinery, New York, NY, USA, 283–291. doi: 10.1145/3524458.3547230.
WhaleAnalytica leverages the transparency of the blockchain to provide real-world data and unique insights into the Web 3.0 digital asset market.
Swiss Engineering 🇨🇭
Geneva and Lausanne