A new layer of complexity in time-evolving systems?

What is it about?

In the study of online communities, such as the Wikipedia encyclopedia or the Zooniverse citizen science platform, it has been found that constructing temporally ordered networks of information token recurrence can help to detect real-world events or capture formerly hidden structures of collective activity. In this article we describe the practical and principled foundations of a new approach to analyse sequential data in abstraction from any social or application-dependent context. We also explain why it challenges the epistemological assumptions of contemporary analytical approaches by linking it to the philosophy of truth.

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Why is it important?

The approach described here, called Transcendental Information Cascades, make formerly hidden layers of complexity in sequential data accessible, and throws up novel questions about chaos and randomness in any kind of time-evolving complex system.