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Special Issue:
SPECIAL TOPIC — Computational programs in complex systems
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| SPECIAL TOPIC — Computational programs in complex systems |
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Evolutionary role of startups and its relevance to the success in the blockchain field based on temporal information networks |
| Ying Wang(王颖)1 and Qing Guan(管青)2,† |
1 School of Economics and Management, China University of Geosciences, Beijing 100083, China;
2 School of Information Engineering, China University of Geosciences, Beijing 100083, China |
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Abstract Startups form an information network that reflects their growth trajectories through information flow channels established by shared investors. However, traditional static network metrics overlook temporal dynamics and rely on single indicators to assess startups' roles in predicting future success, failing to comprehensively capture topological variations and structural diversity. To address these limitations, we construct a temporal information network using 14547 investment records from 1013 global blockchain startups between 2004 and 2020, sourced from Crunchbase. We propose two dynamic methods to characterize the information flow: temporal random walk (sTRW) for modeling information flow trajectories and temporal betweenness centrality (tTBET) for identifying key information hubs. These methods enhance walk coverage while ensuring random stability, allowing for more effective identification of influential startups. By integrating sTRW and tTBET, we develop a comprehensive metric to evaluate a startup's influence within the network. In experiments assessing startups' potential for future success—where successful startups are defined as those that have undergone M&A or IPO—incorporating this metric improves accuracy, recall, and F1 score by 0.035, 0.035, and 0.042, respectively. Our findings indicate that information flow from key startups to others diminishes as the network distance increases. Additionally, successful startups generally exhibit higher information inflows than outflows, suggesting that actively seeking investment-related information contributes to startup growth. Our research provides valuable insights for formulating startup development strategies and offers practical guidance for market regulators.
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Received: 31 December 2024
Revised: 09 April 2025
Accepted manuscript online: 30 April 2025
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PACS:
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89.65.Gh
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(Economics; econophysics, financial markets, business and management)
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07.05.Tp
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(Computer modeling and simulation)
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| Fund: The authors are grateful for the funding from the National Natural Science Foundation of China (Grant Nos. 42001236, 71991481, and 71991480) and Young Elite Scientist Sponsorship Program by Bast (Grant No. BYESS2023413). |
Corresponding Authors:
Qing Guan
E-mail: guanqing35@126.com
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Cite this article:
Ying Wang(王颖) and Qing Guan(管青) Evolutionary role of startups and its relevance to the success in the blockchain field based on temporal information networks 2025 Chin. Phys. B 34 088901
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