What an Entangled Web We Weave: An Information-centric Approach to Time-evolving Socio-technical Systems
A new layer of complexity, constituted of networks of information token recurrence, has been identified in socio-technical systems such as the Wikipedia online community and the Zooniverse citizen science platform. The identification of this complexity reveals that our current understanding of the actual structure of those systems, and consequently the structure of the entire World Wide Web, is incomplete, which raises novel questions for data science research but also from the perspective of social epistemology. Here we establish the principled foundations and practical advantages of analyzing information diffusion within and across Web systems with Transcendental Information Cascades, and outline resulting directions for future study in the area of socio-technical systems. We also suggest that Transcendental Information Cascades may be applicable to any kind of time-evolving system that can be observed using digital technologies, and that the structures found in such systems comprise properties common to all naturally occurring complex systems.
KeywordsInformation Philosophy Temporal data mining Bursts Information dynamics Socio-technical systems Information theory Information cascades Complexity science Network science Epistemology Knowledge Truth Time
This article underwent an extensive open peer-review process, because the initial version was published as a pre-print on PeerJ (https://doi.org/10.7287/peerj.preprints.2789). The authors want thank all people who took the time to provide critical comments and feedback about this version or who engaged in discussions when the argument was presented at scientific events. Our work was partially supported under SOCIAM: The Theory and Practice of Social Machines, funded by the UK EPSRC under Grant EP/J017728/2 and the Victoria University of Wellington Research Establishment Grant 8-1620-213486-3744.
- Bailey, K. D. (1990). Social entropy theory. Albany: SUNY Press.Google Scholar
- Barabasi, A.-L. (2005). The origin of bursts and heavy tails in human dynamics. arXiv:cond-mat/0505371.
- Berners-Lee, T., Fischetti, M., & Dertouzos, M. L. (2000). Weaving the web: The original design and ultimate destiny of the World Wide Web by its inventor. New York: HarperInformation.Google Scholar
- Cheng, J., Adamic, L., Dow, P. A., Kleinberg, J. M., & Leskovec, J. (2014). Can cascades be predicted? In Proceedings of the 23rd international conference on World wide web (pp. 925–936). ACM.Google Scholar
- Dinneen, J. D. & Brauner, C. (2017). Information-not-thing: further problems with and alternatives to the belief that information is physical. In CAIS-ACSI ‘17: Proceedings of the 2017 Canadian Association for Information Science.Google Scholar
- Honari, A. (2015). Online social research in Iran: A need to offer a bigger picture. CyberOrient: The Online Journal of Virtual Middle East, 9(2).Google Scholar
- Jung, C. G. (2010). Synchronicity: An acausal connecting principle. (From Vol. 8. of the collected works of CG Jung) (New in Paper). Princeton: Princeton University Press.Google Scholar
- Kant, I. (1934). Critique of pure reason. (Trans: Smith, N. K.). London: Macmillan.Google Scholar
- Keegan, B. C., Lev, S., & Arazy, O. (2016). Analyzing organizational routines in online knowledge collaborations: A case for sequence analysis in CSCW. In Proceedings of the 19th ACM conference on computer-supported cooperative work & social computing (pp. 1065–1079). ACM.Google Scholar
- Kraut, R. E., Resnick, P., Kiesler, S., Burke, M., Chen, Y., Kittur, N., et al. (2012). Building successful online communities: Evidence-based social design. Cambridge: MIT Press.Google Scholar
- Lee, C. P. & Paine, D. (2015). From the matrix to a model of coordinated action (moca): A conceptual framework of and for CSCW. In Proceedings of the 18th ACM conference on computer supported cooperative work & social computing (pp. 179–194). ACM.Google Scholar
- Lee, E., Karimi, F., Jo, H.-H., Strohmaier, M., & Wagner, C. (2017). Homophily explains perception biases in social networks. arXiv:1710.08601.
- Luczak-Roesch, M., Tinati, R., & Shadbolt, N. (2015b). When resources collide: Towards a theory of coincidence in information spaces. In Proceedings of the 24th international conference on world wide web (pp. 1137–1142). ACM.Google Scholar
- Luczak-Roesch, M., Tinati, R., O’Hara, K., & Shadbolt, N. (2015a). Socio-technical computation. In Proceedings of the 18th ACM conference companion on computer supported cooperative work & social computing (pp. 139–142). ACM.Google Scholar
- Luczak-Roesch, M., Tinati, R., Simperl, E., Van Kleek, M., Shadbolt, N., & Simpson, R. J. (2014). Why won’t aliens talk to us? content and community dynamics in online citizen science. In ICWSM.Google Scholar
- Luczak-Roesch, M., Tinati, R., Van Kleek, M., & Shadbolt, N. (2015c). From coincidence to purposeful flow? properties of transcendental information cascades. In Proceedings of the 2015 IEEE/ACM international conference on advances in social networks analysis and mining 2015 (pp. 633–638). ACM.Google Scholar
- Malone, T. W., Laubacher, R., & Dellarocas, C. (2009). Harnessing crowds: Mapping the genome of collective intelligence. Technical Report No. 4732-09, MIT Sloan Research Paper.Google Scholar
- McLuhan, M., & Fiore, Q. (1967). The medium is the message. New York, 123, 126–128.Google Scholar
- Pettit, P. (2010). Groups with minds of their own. In A. I. Goldman & D. Whitcomb (Eds.), Social epistemology: Essential readings (p. 242). Oxford: Oxford University Press.Google Scholar
- Popper, K. (1972). Objective knowledge: An evolutionary approach. Oxford University Press.Google Scholar
- Popper, K. (2013). Knowledge and the body-mind problem: In defence of interaction. London: Routledge.Google Scholar
- Potthast, M., Stein, B., & Gerling, R. (2008). Automatic vandalism detection in wikipedia. In European conference on information retrieval (pp. 663–668). Springer.Google Scholar
- Quinn, A. J. & Bederson, B. B. (2011). Human computation: A survey and taxonomy of a growing field. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 1403–1412). ACM.Google Scholar
- Shahaf, D., Yang, J., Suen, C., Jacobs, J., Wang, H., & Leskovec, J. (2013). Information cartography: Creating zoomable, large-scale maps of information. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1097–1105). ACM.Google Scholar
- Smart, P., Simperl, E., & Shadbolt, N. (2014). A taxonomic framework for social machines. In D. Miorandi, V. Maltese, M. Rovatsos, A. Nijholt, & J. Stewart (Eds.), Social collective intelligence (pp. 51–85). Cham: Springer.Google Scholar
- Tinati, R., & Luczak-Roesch, M. (2017). Wikipedia: A complex social machine. SIGWEB Newsletter, Winter, 6. https://doi.org/10.1145/3027141.3027147.
- Tinati, R., Luczak-Roesch, M., & Hall, W. (2016). Finding structure in wikipedia edit activity: An information cascade approach. In Proceedings of the 25th international conference companion on world wide web (pp. 1007–1012). International World Wide Web Conferences Steering Committee.Google Scholar
- Tinati, R., Luczak-Roesch, M., Shadbolt, N., & Hall, W. (2015a). Using wikiprojects to measure the health of wikipedia. In Proceedings of the 24th international conference on world wide web (pp. 369–370). ACM.Google Scholar
- Tinati, R., Van Kleek, M., Simperl, E., Luczak-Rösch, M., Simpson, R., & Shadbolt, N. (2015b). Designing for citizen data analysis: A cross-sectional case study of a multi-domain citizen science platform. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 4069–4078). ACM.Google Scholar
- Van de Sompel, H., Nelson, M., & Sanderson, R. (2013). HTTP framework for time-based access to resource states–Memento. No. RFC 7089. https://www.rfc-editor.org/info/rfc7089.
- Van de Sompel, H., Nelson, M. L., Sanderson, R., Balakireva, L. L., Ainsworth, S., & Shankar, H. (2009). Memento: Time travel for the web. arXiv:0911.1112.
- Webber Jr, C. L. & Zbilut, J. P. (2005). Recurrence quantification analysis of nonlinear dynamical systems. In Tutorials in contemporary nonlinear methods for the behavioral sciences (pp. 26–94). National Science Foundation.Google Scholar
- Weber, M. (1978). Economy and society: An outline of interpretive sociology (Vol. 1). Berkeley: University of California Press.Google Scholar