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A Natural Language Processing Approach to Social License Management

Author

Listed:
  • Robert G. Boutilier

    (Stakeholder360, Cuernavaca 62810, Mexico)

  • Kyle Bahr

    (Graduate School of Environmental Studies, Tohoku University, Sendai 980-0845, Japan)

Abstract

Dealing with the social and political impacts of large complex projects requires monitoring and responding to concerns from an ever-evolving network of stakeholders. This paper describes the use of text analysis algorithms to identify stakeholders’ concerns across the project life cycle. The social license (SL) concept has been used to monitor the level of social acceptance of a project. That acceptance can be assessed from the texts produced by stakeholders on sources ranging from social media to personal interviews. The same texts also contain information on the substance of stakeholders’ concerns. Until recently, extracting that information necessitated manual coding by humans, which is a method that takes too long to be useful in time-sensitive projects. Using natural language processing algorithms, we designed a program that assesses the SL level and identifies stakeholders’ concerns in a few hours. To validate the program, we compared it to human coding of interview texts from a Bolivian mining project from 2009 to 2018. The program’s estimation of the annual average SL was significantly correlated with rating scale measures. The topics of concern identified by the program matched the most mentioned categories defined by human coders and identified the same temporal trends.

Suggested Citation

  • Robert G. Boutilier & Kyle Bahr, 2020. "A Natural Language Processing Approach to Social License Management," Sustainability, MDPI, vol. 12(20), pages 1-12, October.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:20:p:8441-:d:427417
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    References listed on IDEAS

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    1. John Morrison, 2014. "The Social License," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-37072-3.
    2. Buah, Eric & Linnanen, Lassi & Wu, Huapeng, 2020. "Emotional responses to energy projects: A new method for modeling and prediction beyond self-reported emotion measure," Energy, Elsevier, vol. 190(C).
    3. Robert G. Boutilier & Michal Zdziarski, 2017. "Managing stakeholder networks for a social license to build," Construction Management and Economics, Taylor & Francis Journals, vol. 35(8-9), pages 498-513, September.
    4. John Morrison, 2014. "The social license," Palgrave Macmillan Books, in: The Social License, chapter 0, pages 12-28, Palgrave Macmillan.
    5. Stephen Ward & Chris Chapman, 2008. "Stakeholders and uncertainty management in projects," Construction Management and Economics, Taylor & Francis Journals, vol. 26(6), pages 563-577.
    6. Beatriz Muriel & Miguel Fernández Moscoso, 2014. "¿Es Posible Construir Beneficios Mutuos entre Comunidades y Empresas Mineras?: El Caso San Cristóbal," Development Research Working Paper Series 05/2014, Institute for Advanced Development Studies.
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    Cited by:

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