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The Lean Research: How to Design and Execute Social Collective Intelligence Research and Innovation Projects

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Social Collective Intelligence

Part of the book series: Computational Social Sciences ((CSS))

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Abstract

In this chapter we advocate the use of a research methodology, that we term ‘the lean research’, for research and innovation projects in the field of Social Collective Intelligence. Motivated by the unique features of Social Collective Intelligence setting, in particular its people-centric nature and its multidisciplinary character, we propose a set of guidelines for maximising the success chances and the potential impacts of projects in the field. A parallel with the ‘lean startup’ approach currently getting popular among Web entrepreneurs and high-tech companies is used extensively throughout the chapter.

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Notes

  1. 1.

    http://social-ist.eu/.

  2. 2.

    An interesting and open research question is to understand the minimum sample size for validating a given research hypothesis in SCI.

  3. 3.

    https://www.mturk.com/mturk/welcome.

References

  1. Blank, S.: Why the lean start-up changes everything. Harv. Bus. Rev. 91(5), 63–72 (2013)

    Google Scholar 

  2. Carreras, I., Anderson, S., Robertson, D., Miorandi, D.: Roadmap for FET initiatives in social collective intelligence (2013). URL http://social-ist.eu/files/2013/12/D3.1.pdf. Social-IST FP7 Project Deliverable D3.1

  3. Chesbrough, H.W.: Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business Press, Boston (2003)

    Google Scholar 

  4. DeBellis, M., Haapala, C.: User-centric software engineering. IEEE Expert 10(1), 34–41 (1995)

    Article  Google Scholar 

  5. Edler, J., Georghiou, L.: Public procurement and innovation-resurrecting the demand side. Res. Pol. 36(7), 949–963 (2007)

    Article  Google Scholar 

  6. Eriksson, M., Niitamo, V.P., Kulkki, S.: State-of-the-Art in Utilizing Living Labs Approach to User-Centric Ict Innovation-a European Approach. Lulea: Center for Distance-spanning Technology. Lulea University of Technology Sweden, Lulea. Online under: http://www.cdt.ltu.se/main.php/SOA_LivingLabs.pdf (2005)

  7. Fowler, M., Highsmith, J.: The agile manifesto. Software Dev. 9(8), 28–35 (2001)

    Google Scholar 

  8. Galilei, G.: Discorsi e dimostrazioni matematiche, intorno à due nuove scienze (discourses and mathematical demonstrations relating to two new sciences). Leiden (1638)

    Google Scholar 

  9. Guidelines on open access to scientific publications and research data in Horizon 2020 (2013). URL http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020- hi-oa-pilot-guide_en.pdf

  10. Hartswood, M., Grimpe, B., Jirotka, M., Anderson, S.: Towards the ethical governance of smart society. In: Miorandi, D., Maltese, V., Rovatsos, M., Nijholt, A., Stewart, J. (eds.) Social Collective Intelligence: Combining the Powers of Humans and Machines to Build a Smarter Society. Springer, New York (2014)

    Google Scholar 

  11. Hufford, M.E.: The romance of research. School Sci. Math. 35(3), 273–284 (1935)

    Article  Google Scholar 

  12. Kittur, A., Chi, E.H., Suh, B.: Crowdsourcing user studies with Mechanical Turk. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 453–456. ACM, New York (2008)

    Google Scholar 

  13. Kothari, C.: Research Methodology: Methods and Techniques. New Age International, New Delhi (2004)

    Google Scholar 

  14. Kulkarni, A.P., Can, M., Hartmann, B.: Turkomatic: automatic recursive task and workflow design for mechanical turk. In: CHI’11 Extended Abstracts on Human Factors in Computing Systems, pp. 2053–2058. ACM, New York (2011)

    Google Scholar 

  15. Kumar, S., Phrommathed, P.: Research Methodology. Springer, New York (2005)

    Google Scholar 

  16. Little, G., Chilton, L.B., Goldman, M., Miller, R.C.: Turkit: tools for iterative tasks on mechanical turk. In: Proceedings of the ACM SIGKDD Workshop on Human Computation, pp. 29–30. ACM, New York (2009)

    Google Scholar 

  17. Maguire, M.: Methods to support human-centred design. Int. J. Hum. Comput. Stud. 55(4), 587–634 (2001)

    Article  MATH  Google Scholar 

  18. Mason, W., Suri, S.: Conducting behavioral research on Amazon’s mechanical turk. Behav. Res. Meth. 44(1), 1–23 (2012)

    Article  Google Scholar 

  19. Owen, R., Macnaghten, P., Stilgoe, J.: Responsible research and innovation: From science in society to science for society, with society. Sci. Publ. Pol. 39(6), 751–760 (2012)

    Article  Google Scholar 

  20. Paolacci, G., Chandler, J., Ipeirotis, P.G.: Running experiments on Amazon Mechanical Turk. Judgment Decis. Making 5(5), 411–419 (2010)

    Google Scholar 

  21. Ries, E.: The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. Random House LLC, New York, NY (US) (2011)

    Google Scholar 

  22. Rigby, J.: Review of pre-commercial procurement approaches and effects on innovation. Tech. Rep. Working Paper 13/14, NESTA (2013). URL http://www.nesta.org.uk/sites/default/files/review_of_pre-commercial_procurement_approaches_and_effects_on_innovation_revised_ajr-14-11-2013_final.pdf

  23. Robertson, D., Anderson, S., Carreras, I., Miorandi, D.: White paper on research challenges in social collective intelligence (2013). URL http://social-ist.eu/files/2013/12/D2.1.pdf. Social-IST FP7 Project Deliverable D2.1

  24. Roy, R., Goatman, M., Khangura, K.: User-centric design and kansei engineering. CIRP J. Manuf. Sci. Tech. 1(3), 172–178 (2009)

    Article  Google Scholar 

  25. Sanders, E.B.N., Stappers, P.J.: Co-creation and the new landscapes of design. Co-design 4(1), 5–18 (2008)

    Google Scholar 

  26. Scekic, O., Truong, H.L., Dustdar, S.: Incentives and rewarding in social computing. Comm. ACM 56(6), 72–82 (2013)

    Article  Google Scholar 

  27. Schumpeter, J.A.: Business Cycles, vol. 1. Cambridge Univ Press, Cambridge (1939)

    Google Scholar 

  28. Uhlir, P., Schröder, P.: Open data for global science. Data Sci. J. 6(0) (2007)

    Google Scholar 

  29. Vespignani, A.: Predicting the behavior of techno-social systems. Science 325(5939), 425 (2009)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The work reported here was partially supported by the European Community’s Seventh Framework Program (FP7/2007–2013) under grant agreement n. 317681 Social-IST: Social Collective Intelligence (http://social-ist.eu/).

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Authors and Affiliations

  1. CREATE-NET, v. alla Cascata 56/D, 38123—Povo, Trento, Italy

    Daniele Miorandi, Iacopo Carreras & Imrich Chlamtac

Authors
  1. Daniele Miorandi
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  2. Iacopo Carreras
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  3. Imrich Chlamtac
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Corresponding author

Correspondence to Daniele Miorandi .

Editor information

Editors and Affiliations

  1. CREATE-NET, Trento, Italy

    Daniele Miorandi

  2. University of Trento, Trento, Italy

    Vincenzo Maltese

  3. School of Informatics Informatics, The University of Edinburgh, Edinburgh, United Kingdom

    Michael Rovatsos

  4. Faculty EEMCS, University of Twente, Enschede, The Netherlands

    Anton Nijholt

  5. The University of Edinburgh, Edinburgh, United Kingdom

    James Stewart

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Miorandi, D., Carreras, I., Chlamtac, I. (2014). The Lean Research: How to Design and Execute Social Collective Intelligence Research and Innovation Projects. In: Miorandi, D., Maltese, V., Rovatsos, M., Nijholt, A., Stewart, J. (eds) Social Collective Intelligence. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-08681-1_13

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  • DOI: https://doi.org/10.1007/978-3-319-08681-1_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08680-4

  • Online ISBN: 978-3-319-08681-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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