Skip to main content
SpringerLink
Log in

Towards Bottom-Up Decision Making and Collaborative Knowledge Generation in Urban Infrastructure Projects Through Online Social Media

  • Chapter
Transparency in Social Media

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

Abstract

Evolution of civil infrastructure from a technical artifact into an engineering system and a national asset over the past century has created a new discourse for development, construction, and management of infrastructure, which more and more emphasizes soft and subjective aspects of the system. Modern civil infrastructure is a complex system composed of the physical network of assets together with the social network of actors/users, and their interactions through the operational processes of the system (Lukszo & Bouwmas, 2005). This defines a sociotechnical system whose behavior cannot be studied without respect to the associated agents and the related social/institutional infrastructure. This system will be governed by organizational policies as well as social norms and standards. Such a definition for civil infrastructure has improved the role of the society from customers and end users of a service into stakeholders who may influence specifications of the system. This new role introduces new opportunities and challenges to domain decision makers. On one hand, it creates great opportunities for social engagement. Technical and professional decision makers can distill the distributed knowledge of public communities (referred to as non-expert or non-mainstream knowledge by Brabham & Sanchez, 2010) to reinforce the decision making procedure. On the other hand, given the diversity of interests and technical sophistications involved, an active participation of the public may result in a chaotic nature for the decision process.

Watch a man at play for an hour and you can learn more about him than in talking to him for a year.

—Plato

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Traditional methods in PI mostly rely on pushing end-users via survey questionnaires and other tools to contribute inputs to the decision making procedure, as well as trying to educate them about the project related decisions and then collect their feedback during public hearings and community meetings. In all these methods, contributors “react” to the initiators within a defined scope and specific framework.

References

  • Atkinson, G. M., & Wald, D. J. (2007). Did you feel it? Intensity data: A surprisingly good measure of earthquake ground motion. Seismological Research Letters, 78, 362–368.

    Article  Google Scholar 

  • Brabham, D. C., & Sanchez, T. W. (2010). Crowdsourcing public participation in transit planning: preliminary results from The Next Stop design case. TRB 89th annual meeting. Washington, DC: Transportation Research Board of the National Academies.

    Google Scholar 

  • Bregman, S., & Watkins, K. (2013). Best practices for transportation agency use of social media. Boca Raton, FL: CRC Press.

    Book  Google Scholar 

  • Bruijn, H. D., & Heuvelhof, E. T. (2000). Networks and decision making. Utrecht: Lemma Publishers.

    Google Scholar 

  • Chinowsky, P., Diekmann, J., & Galotti, V. (2008). Social network model of construction. ASCE Journal of Construction Engineering & Management, 134, 804–812.

    Article  Google Scholar 

  • Chinowsky, P., Diekmann, J., & O’Brien, J. (2010). Project organizations as social networks. Journal of Construction Engineering and Management, 136(SPECIAL ISSUE: Governance and leadership challenges of global construction), 452–458.

    Google Scholar 

  • Crooks, A., Croitoru, A., Stefanidis, A., & Radzikowski, J. (2013). #Earthquake: Twitter as a distributed sensor system. Transactions in GIS, 17, 124–147.

    Article  Google Scholar 

  • Di Marco, M. K., Taylor, J. E., & Alin, P. (2010). Emergence and role of cultural boundary spanners in global engineering project networks. Journal of Management in engineering, 26(3), 123–132.

    Article  Google Scholar 

  • Easley, D., & Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. New York: Cambridge University Press.

    Book  Google Scholar 

  • El-Diraby, T. E. (2011). Civil infrastructure as a chaotic socio-technical system: How can information systems support collaborative innovation. CIBW078. Computer Knowledge Building.

    Google Scholar 

  • Evans-Cowley, J. S. (2012). Griffin G. Microparticipation with social media for community engagement in trasportation planning., 2307, 90–98.

    Google Scholar 

  • Evans-Cowley, J., & Griffin, G. (2011, Feb 12). Micro-participation: The role of microblogging in planning. Retrieved Feb 27, 2014, from SSRN: http://ssrn.com/abstract=1760522 or http://dx.doi.org/10.2139/ssrn.1760522

  • Future by airbus. (2012). Retrieved February 20, 2014, from Airbus.com: http://www.airbus.com/innovation/future-by-airbus/.

  • Hansen, J. S., & Jackson, M. C. (2001). St. Louis redefines community engagement. Land Development and Public Involvement in Transportation, 1780, 140–144.

    Google Scholar 

  • Huberman, B. A., Romero, D. M., & Fang, W. (2008). Social networks that matter: Twitter under the microscope. First Monday, 14(1), 1–9.

    Article  Google Scholar 

  • Huberman, B. A., Romero, D. M., & Wu, F. (2009). Social networks that matter: Twitter under the microscope. First Monday, 14(1), 8.

    Google Scholar 

  • Keast, R., & Hampson, K. (2007). Building construction innovation networks: Role of relationship management. ASCE Journal of Construction Engineering & Management, 133, 364–373.

    Article  Google Scholar 

  • KTOC. (2010). Retrieved February 26, 2014, from FHWA Transportation library connectivity: http://libraryconnectivity.org/archive/downloads/KTOC-Poster.pdf.

  • Levitt, R. E. (2007). CEM research for the next 50 years: Maximizing economic, environmental, and societal value of the built environment. ASCE Journal of Construction Engineering and Management, 133, 619–628.

    Article  Google Scholar 

  • Levitt, R. E. (2011). Towards project management 2.0. In Engineering project organizations conference. Denver, CO: EPOC.

    Google Scholar 

  • Lorenz, J. (2011). Building support for new transportation funding and financing program. Transportation Research Records, 2245, 8–16.

    Article  Google Scholar 

  • Lukszo, Z. V., & Bouwmas, I. (2005). Intelligent complexity in networked infrastructure. IEEE international conference on Systems, Man and Cybernetics, (pp. 2378–2383). Waikoloa Village, HI: IEEE.

    Google Scholar 

  • Nik Bakht, M., & El-diraby, T. (2014). Infrastructure discussion networks: Analyzing social media debates of LRT projects in North American cities. TRB 3rd annual meeting compendium of papers. Washington, DC: TRB.

    Google Scholar 

  • Nik Bakht, M., & El-diraby, T. E. (2013a). Analyzing infrastructure discussion networks: order of ‘influence’ in chaos of ‘followers’. Csce annual conference-4th construction specialty conference . Montreal: CSCE.

    Google Scholar 

  • Nik Bakht, M., & El-Diraby, T. E. (2013b). What does social media say about the infrastructure construction project? Beijing, China: CIB W78.

    Google Scholar 

  • NYC Bike Share. (2012). Retrieved February 26, 2014, from NYCDOT: http://a841-tfpweb.nyc.gov/bikeshare/suggestion-archive/.

  • Olander, S. (2007). Stakeholder impact analysis in construction project management. Construction Management and Exonomicsa, 25, 277–287.

    Article  Google Scholar 

  • Quinn, P. (2012, Jan 06). Kansas department of transportation—Northeast Kansas. Retrieved February 27, 2014, from Facebook: https://www.facebook.com/NEKansasKDOT/posts/146758275436663.

  • Sanvido, V. E., & Paulson, B. C. (1992). Site-level construction information system. ASCE Journal of Construction Engineering and Management, 118, 701–715.

    Article  Google Scholar 

  • Slaughter, S. E. (1993). Builders as sources of construction innovation. ASCE Journal of Construction Engineering and Management, 119, 532–549.

    Article  Google Scholar 

  • Sousa, A. O. (2005). Consensus formation on a triad scale-free network. Physica A, 348, 701–710.

    Article  Google Scholar 

  • Steinhaeuser, K., & Chawla, N. V. (2008). Community detection in a large real-world social network. In International conference on social computing, behavioral modeling and prediction (pp. 168–175). Phoenix, AZ: Springer.

    Google Scholar 

  • Von Hippel, E. (2005). Democratizing innovation. Cambridge, MA: MIT Press.

    Google Scholar 

  • Wagner, J. (2013). Measuring the performance of public engagement in transportation planning: Three best principles. Journal of the Transportation Research Board, 2397, 38–44.

    Article  Google Scholar 

  • Wambeke, B. W., Liu, M., & Hsiang, S. M. (2012). Using Pajek and centrality analysis to identify a social network of construction trades. ASCE Journal of Construction Engineering and Management, 138(10), 1192–1201.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Toronto, Toronto, ON, Canada

    Mazdak Nik-Bakht

  2. Department of Civil Engineering, University of Toronto, Toronto, ON, Canada

    Tamer E. El-Diraby

Authors
  1. Mazdak Nik-Bakht
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tamer E. El-Diraby
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mazdak Nik-Bakht .

Editor information

Editors and Affiliations

  1. Purdue University, West Lafayette, Indiana, USA

    Sorin Adam Matei

  2. mediaX, Stanford University, Stanford, California, USA

    Martha G. Russell

  3. Computer Science, Purdue University, West Lafayette, Indiana, USA

    Elisa Bertino

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Nik-Bakht, M., El-Diraby, T.E. (2015). Towards Bottom-Up Decision Making and Collaborative Knowledge Generation in Urban Infrastructure Projects Through Online Social Media. In: Matei, S., Russell, M., Bertino, E. (eds) Transparency in Social Media. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-18552-1_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-18552-1_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18551-4

  • Online ISBN: 978-3-319-18552-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation