Quantified Us: a group-in-the-loop approach to team network reconstruction

by | Sep 1, 2021 | Research Publications

Author(s):

Raphael Tackx

Leo Blondel

Marc Santolini

Abstract:

Understanding team collaboration processes is key for the development of new technologies towards increasing groups effectiveness. In particular, the need and challenges of coordinating potentially large-scale, self-organized, collaborative initiatives have been made even more salient by the COVID-19 pandemic. Key to this challenge is the difficulty for participants to situate themselves within the larger social context. At the individual level, the Quantified-Self movement has showcased how insights from one’s own data can trigger changes in behavior, sometimes leading to fundamental insights through self-research. Building on these premises, here we present CoSo (Collaborative Sonar), a digital platform for participatory collective sensing and social research. CoSo is a web and mobile data collection platform for team network reconstruction and visualization. It leverages a “group-in-the-loop” intrinsic motivator to collect data on collaborative activities performed by a team through a mobile app, with summary statistics and visualizations of the collected data made available on a web dashboard. We showcase its use and discuss the perspectives offered by promoting group-level metacognition and collective introspection. By highlighting the invisible relationships in a group, CoSo facilitates in-the-wild studies, remote/hybrid data collection, and multi-modal sensing approaches of group interactions within professional and other social contexts.

Documentation:

https://doi.org/10.1145/3460418.3479363

References:
  1. Daniel Barkoczi and Mirta Galesic. 2016. Social learning strategies modify the effect of network structure on group performance. Nat. Commun. 7 (Oct. 2016), 13109.
  2. Alain Barrat, Ciro Cattuto, Vittoria Colizza, Jean-Francois Pinton, Wouter Van den Broeck, and Alessandro Vespignani. 2008. High resolution dynamical mapping of social interactions with active RFID. (Nov. 2008). arxiv:0811.4170 [cs.CY]
  3. Vincent D Blondel, Adeline Decuyper, and Gautier Krings. 2015. A survey of results on mobile phone datasets analysis. EPJ Data Science 4, 1 (Aug. 2015), 10.
  4. Vincent D Blondel, Jean-Loup Guillaume, Renaud Lambiotte, and Etienne Lefebvre. 2008. Fast unfolding of communities in large networks. J. Stat. Mech. 2008, 10 (Oct. 2008), P10008.
  5. Tjeerd W Boonstra, Mark E Larsen, and Helen Christensen. 2015. Mapping dynamic social networks in real life using participants’ own smartphones. Heliyon 1, 3 (Nov. 2015), e00037.
  6. J Brown. 2007. The iGEM competition: building with biology. IET Synth. Biol. 1, 1 (June 2007), 3–6.
  7. Mathieu Cunche, Antoine Boutet, Claude Castelluccia, Cédric Lauradoux, and Vincent Roca. 2020. On using Bluetooth-Low-Energy for contact tracing. Research Report. Inria Grenoble Rhône-Alpes ; INSA de Lyon. https://hal.inria.fr/hal-02878346
  8. Pierre Deville, Dashun Wang, Roberta Sinatra, Chaoming Song, Vincent D Blondel, and Albert-László Barabási. 2014. Career on the move: geography, stratification, and scientific impact. Sci. Rep. 4 (April 2014), 4770.
  9. Chiara Franzoni and Henry Sauermann. 2014. Crowd science: The organization of scientific research in open collaborative projects. Res. Policy 43, 1 (Feb. 2014), 1–20.
  10. Fosca Giannotti, Luca Pappalardo, Dino Pedreschi, and Dashun Wang. 2013. A Complexity Science Perspective on Human Mobility.
  11. Bastian Greshake Tzovaras, Misha Angrist, Kevin Arvai, Mairi Dulaney, Vero Estrada-Galiñanes, Beau Gunderson, Tim Head, Dana Lewis, Oded Nov, Orit Shaer, Athina Tzovara, Jason Bobe, and Mad Price Ball. 2019. Open Humans: A platform for participant-centered research and personal data exploration. Gigascience 8, 6 (June 2019).
  12. R Guimera. 2005. Team Assembly Mechanisms Determine Collaboration Network Structure and Team Performance., 697–702 pages.
  13. Saurabh Gupta, Mandeep S Dhillon, Siddhartha Sharma, Riddhi Gohil, and Sunny Sachdeva. 2021. Epicollect5: A Free, Fully Customizable Mobile-based Application for Data Collection in Clinical Research., 248–251 pages.
  14. Arno Klein, Jon Clucas, Anirudh Krishnakumar, Satrajit S Ghosh, Wil Van Auken, Benjamin Thonet, Ihor Sabram, Nino Acuna, Anisha Keshavan, Henry Rossiter, Yao Xiao, Sergey Semenuta, Alessandra Badioli, Kseniia Konishcheva, Sanu Ann Abraham, Lindsay M Alexander, Kathleen R Merikangas, Joel Swendsen, Ariel B Lindner, and Michael P Milham. 2020. Remote Digital Psychiatry: MindLogger for Mobile Mental Health Assessment and Therapy. (Nov. 2020), 2020.11.16.385880 pages.
  15. Michael Klug and James P Bagrow. 2016. Understanding the group dynamics and success of teams. R Soc Open Sci 3, 4 (April 2016), 160007.
  16. Camille M Masselot, Bastian Greshake Tzovaras, Chris L B Graham, Gary Finnegan, Rathin Jeyaram, Isabelle Vitali, Thomas E Landrain, and Marc Santolini. 2021. Co-Immune: a case study on open innovation for vaccination hesitancy and access. medRxiv (2021).
  17. Staša Milojević. 2014. Principles of scientific research team formation and evolution. Proc. Natl. Acad. Sci. U. S. A. 111, 11 (March 2014), 3984–3989.
  18. Michael Nielsen. 2011. Reinventing Discovery.
  19. J G Oliveira and A-L Barabási. 2005. Human Dynamics: The Correspondence Patterns of Darwin and Einstein. (Nov. 2005). arxiv:physics/0511006 [physics.soc-ph]
  20. Pentland, A. 2012. The new science of building great teams. Harv. Bus. Rev. 90, 4 (2012), 60–69.
  21. Barbara Pernici. 2020. CROWD4SDG: Crowdsourcing for sustainable developments goals. Pearson, Upper Saddle River, NJ. 248–252 pages.
  22. Christoph Riedl and Anita Williams Woolley. 2017. Teams vs. Crowds: A Field Test of the Relative Contribution of Incentives, Member Ability, and Emergent Collaboration to Crowd-Based Problem Solving Performance. AMD 3, 4 (Dec. 2017), 382–403.
  23. Shuyun Shi, Debiao He, Li Li, Neeraj Kumar, Muhammad Khurram Khan, and Kim-Kwang Raymond Choo. 2020. Applications of blockchain in ensuring the security and privacy of electronic health record systems: A survey. Computers & Security 97 (Oct. 2020), 101966. https://doi.org/10.1016/j.cose.2020.101966
  24. John Torous, Mathew V Kiang, Jeanette Lorme, and Jukka-Pekka Onnela. 2016. New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research. JMIR Ment Health 3, 2 (May 2016), e16.
  25. Timothy J Trull and Ulrich W Ebner-Priemer. 2020. Ambulatory assessment in psychopathology research: A review of recommended reporting guidelines and current practices., 56–63 pages.
  26. Bastian Greshake Tzovaras, Enric Senabre Hidalgo, Karolina Alexiou, Lukasz Baldy, Basile Morane, Ilona Bussod, Melvin Fribourg, Katarzyna Wac, Gary Wolf, and Mad Ball. 2021. Quantified Flu: an individual-centered approach to gaining sickness-related insights from wearable data. medRxiv (2021).
  27. Brian Uzzi, Stefan Wuchty, Jarrett Spiro, and Benjamin F Jones. 2012. Scientific teams and networks change the face of knowledge creation. In Networks in Social Policy Problems. Cambridge University Press, 47–59.
  28. Duncan Watts. 2016. The organizational spectroscope. Medium, April 1(2016).
  29. Steve Woolgar and Bruno Latour. 1986. Laboratory life: the construction of scientific facts. Princeton University Press.
  30. Anita Williams Woolley, Christopher F Chabris, Alex Pentland, Nada Hashmi, and Thomas W Malone. 2010. Evidence for a collective intelligence factor in the performance of human groups. Science 330, 6004 (Oct. 2010), 686–688.
  31. Stefan Wuchty, Benjamin F Jones, and Brian Uzzi. 2007. The increasing dominance of teams in production of knowledge. Science 316, 5827 (May 2007), 1036–1039.