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Fork-based user migration in Blockchain Online Social Media

Published: 26 June 2022 Publication History

Abstract

Nowadays, Online Social Media (OSM) are among the most popular web services. Traditional OSM are known to be affected by serious issues including misinformation, fake news, censorship, and privacy violations, to the point that a pressing demand for new paradigms is raised by users all over the world. Among such paradigms, the concepts around the Web 3.0 are fueling a new revolution of online sociality, pushing towards the adoption of innovative and groundbreaking technologies. In particular, the decentralization of social services through the blockchain technology is representing the most valid alternative to current OSM, enabling the development of rewarding strategies for value redistribution, and fake news detection. However, the so-called Blockchain Online Social Media (BOSMs) are far from being mature, with different platforms that continually try to redefine their services in order to attract larger audiences, thus causing blockchain forks and massive user migrations, with the latter dominating the dynamics of the current OSM landscape, too.
In this paper, we deal with the evolution of BOSMs from the perspective of user migration across platforms as a consequence of a fork event. We propose a general user migration model applicable to BOSMs to represent the evolution patterns of fork-based migrations, the multi-interaction structural complexity of BOSMs, and their growth characteristics. Within this framework, we also cope with the task of predicting how users will behave in the case of a fork, i.e. they will remain on the original blockchain or they will migrate to the new one. We apply our framework to the case study of the Steem-Hive fork event, and show the importance of considering both social and economic information, regardless of the learning algorithm considered. To the best of our knowledge, this is the first study on blockchain fork and its related user migration.

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Cited By

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  • (2024)On Time-Aware Cross-Blockchain Data MigrationTsinghua Science and Technology10.26599/TST.2023.901013629:6(1810-1820)Online publication date: Dec-2024
  • (2024)Analyzing user migration in blockchain online social networks through network structure and discussion topics of communities on multilayer networksDistributed Ledger Technologies: Research and Practice10.1145/3640020Online publication date: 10-Jan-2024
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            cover image ACM Conferences
            WebSci '22: Proceedings of the 14th ACM Web Science Conference 2022
            June 2022
            479 pages
            ISBN:9781450391917
            DOI:10.1145/3501247
            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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            New York, NY, United States

            Publication History

            Published: 26 June 2022

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            Author Tags

            1. Blockchain Online Social Media
            2. Temporal Networks
            3. User Migration

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            WebSci '22
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            WebSci '22: 14th ACM Web Science Conference 2022
            June 26 - 29, 2022
            Barcelona, Spain

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            Overall Acceptance Rate 245 of 933 submissions, 26%

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            Cited By

            View all
            • (2024)On Time-Aware Cross-Blockchain Data MigrationTsinghua Science and Technology10.26599/TST.2023.901013629:6(1810-1820)Online publication date: Dec-2024
            • (2024)Analyzing user migration in blockchain online social networks through network structure and discussion topics of communities on multilayer networksDistributed Ledger Technologies: Research and Practice10.1145/3640020Online publication date: 10-Jan-2024
            • (2024)Discrete-time graph neural networks for transaction prediction in Web3 social platformsMachine Learning10.1007/s10994-024-06579-y113:9(6395-6412)Online publication date: 25-Jun-2024
            • (2023)Liquid Democracy in DPoS BlockchainsProceedings of the 5th ACM International Symposium on Blockchain and Secure Critical Infrastructure10.1145/3594556.3594606(25-33)Online publication date: 10-Jul-2023
            • (2023)User migration prediction in blockchain socioeconomic networks using graph neural networksProceedings of the 2023 ACM Conference on Information Technology for Social Good10.1145/3582515.3609552(333-341)Online publication date: 6-Sep-2023
            • (2023)User Migration Across Web3 Online Social Networks: Behaviors and Influence of HubsICC 2023 - IEEE International Conference on Communications10.1109/ICC45041.2023.10278763(5595-5601)Online publication date: 28-May-2023
            • (2023)Cross-Consensus Measurement of Individual-level Decentralization in Blockchains2023 IEEE 9th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS)10.1109/BigDataSecurity-HPSC-IDS58521.2023.00018(45-50)Online publication date: May-2023
            • (2023)Drivers of social influence in the Twitter migration to MastodonScientific Reports10.1038/s41598-023-48200-713:1Online publication date: 7-Dec-2023
            • (2023)Cooperative behavior in blockchain-based complementary currency networks through timeFuture Generation Computer Systems10.1016/j.future.2023.05.022148:C(266-279)Online publication date: 1-Nov-2023
            • (2023)Temporal graph learning for dynamic link prediction with text in online social networksMachine Language10.1007/s10994-023-06475-x113:4(2207-2226)Online publication date: 29-Nov-2023
            • Show More Cited By

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