Social Data Analysis

Social Data Analysis

Online Social Networks (OSNs) became part of everyday life for many people around the world. Since their introduction, people have questioned these services because they primarily fail to preserve the users’ privacy. Therefore scientists decided to propose an alternative, distributed architecture, for the implementation of OSN services. A Distributed Online Social Network (DOSN) is an OSNs that does not exploit a central server for the implementation of its services and enables users to have more control over their data, ensuring a higher level of privacy. Thanks to a recent initiative launched by the European Union called Next Generation Internet, online services, such as OSNs, will be re-imagined and re-designed putting the human at the centre of them and then building the service around her/him. To do so, the devices through which the people interact with the services must understand and learn the behaviour of people, and become

the alter ego of their owner. One of the main goals of our team is to study the behaviour of users in order to produce decentralized protocols and algorithms. To do so, our team is studying the behaviour of users in common OSNs, such as Facebook.

Recently, we also investigate the connection between Metaverse and Blockchain. A Metaverse is a shared virtual world, where land, buildings, avatars, and even names can be purchased and sold, sometimes with crypto. People can walk around with their pals, go to facilities, buy goods and services, and attend events in these locations. We are starting to investigate the connection between Metaverse and Non-fungible tokens, both from the perspective of the analysis of the social behaviour of the user in the virtual world and from the point of view of the construction of Layer-2 environment on existing platforms, like Decentraland.


Selected Publications

  • Social games and Blockchain: Exploring the Metaverse of Decentraland, Barbara Guidi and Andrea Michienzi, Int. workshop of Networked Entertainment Systems (NES2022), Best Paper Runner-up Award!

  • Fork-based user migration in Blockchain Online Social Media, Cheick Tidiane Ba, Andrea Michienzi, Barbara Guidi, Matteo Zignani, Laura Ricci, Sabrina Gaito. 14th ACM Web Science Conference, 26-29 June 2022.

  • Predicting Inflential Users in online Social Networks Groups, Barbara Guidi, Andrea De Salve, Roberto DI Pietro, Laura Ricci, accepted for pubblication ACM Transaction on Knowledge Discovery from Data, accepted for publication, 2020.

  • Incremental Communication Patterns in Online Social Groups, Andrea Michienzi, Barbara Guidi, Laura Ricci, Andrea De Salve, Knowledge and Information Systems, Springer, 2021.

  • Analysis of Witness in the Steem Blockchain, Barbara Guidi, Andrea Michienzi, Laura Ricci, Mobile Networks and Applications, Springer, 2021.

  • The Bow Tie Structure of the Bitcoin Users Graph, Damiano Di Francesco Maesa, A. Marino, L. Ricci, Applied Network Science, 2019.

  • Data-driven analysis of bitcoin properties: exploiting the users graph, Damiano Di Francesco Maesa, A. Marino, L. Ricci, International Journal of Data Science and Analytics, 2018

  • A graph-based socio-economic analysis of Steemit, Barbara Guidi, Andrea Michienzi, Laura Ricci, IEEE Transactions on Computational Social Science, 2020.

  • Steem Blockchain: mining the inner structure of the graph, Barbara Guidi, Andrea Michienzi, Laura Ricci, IEEE Access, 2020.


Software and Dataset