Factors Motivating the Public to Participate in Crowdsourcing of Crime Information

  • Authors

    • Badariah Solemon
    • Wan Muhammad Luqman Wan Abu Bakar
    2018-11-30
    https://doi.org/10.14419/ijet.v7i4.35.22917
  • motivation, factor, crowdsourcing, crime information

  • Abstract

    This paper presents the results of an exploratory study conducted to identify the factors that influence people and communities to participate in crowdsourcing approach of crime information. The study uses as survey, self-administered questionnaires distributed to the crowd in the public areas in Selangor and Wilayah Persekutuan, Malaysia as well as through an online survey website. Analysis performed to more than half of 139 valid responses of the survey reveals that the respondents participated in crowdsourced crime reporting and sharing using recent technologies such as mobile application mainly to help reduce the crime rate (nature of problem factor); to contribute to the betterment of mankind and they like the idea of contributing to something of value to the world (altruism factor); to exchange ideas or knowledge on crime information with the crowdsourcing community and to obtain crime related information (learning factor); to share crime related information to others (interest in topic); and to alert others so they can be more cautious (reciprocity factor). Findings from this survey have guided a research work to develop a prototype of mobile application to demonstrate how the application can support neighborhood crime watch activity by enabling community members to share crime incidents information.

  • References

    1. [1] Bendler, J., A. Ratku and D. Neumann (2014). “Crime Mapping through Geo-Spatial Social Media Activity.†In: Proceedings of the 14th International Conferences of Information Systems.

      [2] Hindelang, M. J., Gottfredson, M. R., & Garofalo, J. (1978). Victims of personal crime: An empirical foundation for a theory of personal victimization. Cambridge, MA: Ballinger.

      [3] Cohen LE. Felson. M.(1979). Social change and crime rate trends: A routine activity approach. American Sociological Review. 1979;44(4):588-608.

      [4] Kadar, C., Te, Y.F., Rosés Brüngger, R. and Pletikosa Cvijikj, I., 2016, May. Digital Neighborhood Watch: To share or not to share?. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 2148-2155). ACM.

      [5] Ratcliffe, J. H. (2004). “Crime mapping and the training needs of law enforcement.†European Journal on Criminal Policy and Research 10 (1), 65-83.).

      [6] CrimeReports (2015). URL: https://www.crimereports.com/ (visited on 11/26/2015).

      [7] Crimemapping (2015). URL: http://www.crimemapping.com/ (visited on 11/26/2015).

      [8] Eck, J., S. Chainey, J. Cameron, M. Leitner and R. Wilson (2005). Mapping crime: Understanding hotspots. USA: National Institute of Justice.

      [9] Perry, W. L. (2013). Predictive policing: The role of crime forecasting in law enforcement operations. Rand Corporation.

      [10] WikiCrimes (2015). URL: http://www.wikicrimes.org/ (visited on 11/26/2015).

      [11] CrimePush (2015). URL: http://crimepush.com/ (visited on 11/26/2015).

      [12] Blythe, M. A., P. C. Wright and A. F. Monk (2004). “Little brother: could and should wearable computing technologies be applied to reducing older people’s fear of crime?†Personal and Ubiquitous Computing 8 (6), 402-415.

      [13] Czeskis, A., I. Dermendjieva, H. Yapit, A. Borning, B. Friedman, B. Gill and T. Kohno (2010). “Parenting from the pocket: Value tensions and technical directions for secure and private parent-teen mobile safety.†In: Proceedings of SOUPS.

      [14] Satchell, C. and M. Foth (2011). “Welcome to the jungle: HCI after dark.†In: CHI'11 Extended Abstracts on Human Factors in Computing Systems (pp. 753-762). ACM.

      [15] Blom, J., D. Viswanathan, M. Spasojevic, J. Go, K. Acharya and R. Ahonius (2010). “Fear and the city: role of mobile services in harnessing safety and security in urban use contexts.†In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1841-1850). ACM.

      [16] Ariffin, I., Solemon, I., and Bakar, WMLWA. “An evaluative study on mobile crowdsourcing applications for crime watchâ€. In 2014 International Conference on Information Technology and Multimedia (ICIMU), pp. 335-340. IEEE, 2014.

      [17] Bakar, WMLWA, and Solemon, B. "Exploring the public’s perception towards crowdsourced crime reporting." In the 6th International Conference on Computing and Informatics 2017 (ICOCI2017).

      [18] Howe, J. (2006). The rise of crowdsourcing. Wired magazine, 14(6), 1-4.

      [19] Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business. Economies, Societies and Nations, 296.

      [20] Gebert, M. (2014). Crowdsourcing and Risk-Management.

      [21] Bakar, WMLWA. (2018). A Mobile Crowdsourcing Platform for Facilitating Community Crime Watch. Master Thesis. Universiti Tenaga Nasional.

      [22] Kleemann, F., Voß, G. G., & Rieder, K. (2008). Un (der) paid innovators: The commercial utiliza-tion of consumer work through crowdsourcing. Science, technology & innovation studies, 4(1), PP. 5-26.

      [23] Borromeo, R. M., & Toyama, M. (2016). An investigation of unpaid crowdsourcing. Human-centric Computing and Information Sciences, 6(1), 11.

      [24] Horton, J. J., & Chilton, L. B. (2010). The labor economics of paid crowdsourcing. Proceedings of the 11th ACM Conference on Electronic Commerce.

      [25] Frei, B. (2009). Paid crowdsourcing: Current state & progress toward mainstream business use. Smartsheet White Paper.

      [26] Schenk, E., & Guittard, C. (2011). Towards a characterization of crowdsourcing practices. Journal of Innovation Economics & Management(1), 93-107.

      [27] Vukovic, M., & Bartolini, C. (2010). Towards a research agenda for enterprise crowdsourcing. Paper presented at the International Symposium On Leveraging Applications of Formal Methods, Verification and Validation.

      [28] Deci, E. L., & Ryan, R. M. (1985). The general causality orientations scale: Self-determination in personality. Journal of research in personality, 19(2), 109-134.

      [29] Hossain, M. (2012). Users' motivation to participate in online crowdsourcing platforms. Proceedings of the 2012 International Conference on Innovation Management and Technology Research (ICIMTR).

      [30] Kaufmann, N., Schulze, T., & Veit, D. (2011). More than fun and money. Worker Motivation in Crowdsourcing-A Study on Mechanical Turk. Paper presented at the AMCIS.

      [31] lam, S. L., & Campbell, J. (2012). Crowdsourcing motivations in a not-for-profit GLAM context: the Australian newspapers digitisation program. Paper presented at the ACIS 2012: Location, location, location: Proceedings of the 23rd Australasian Conference on Information Systems 2012.

      [32] Send, H., Friesike, S., & Zuch, A. N. (2014). Participation in On-Line Co-Creation: Assessment and Review of Motivations.

      [33] Zhao, Y., & Zhu, Q. (2012). A Conceptual Model for Participant’s Motivation in Crowdsourcing Contest. Paper presented at the Eleventh Wuhan International Conference on E-business.

      [34] Gourova, E., & Toteva, K. (2011). Raising creativity and participation in innovation and knowledge management activities. Paper presented at the Concurrent Enterprising (ICE), 2011 17th International Conference on.

      [35] Cambridge Dictionary. URL http://dictionary.cambridge.org. (visitied on 05/03/2015).

      [36] Merriam Webster Dictionary. URL https://www.merriam-webster.com. (visited on 05/03/2015).

      [37] Oxford Dictionary. URL https://en.oxforddictionaries.com. (visited on 05/03/2015).

      [38] Beecham, S., Hall, T., & Rainer, A. (2003). Software process improvement problems in twelve software companies: An empirical analysis. Empirical software engineering, 8(1), 7-42.

      [39] Solemon, B. (2012). Requirements Engineering Process Assessment and Improvement Approach for Malay-sian Software Industry (Doctoral dissertation, Universiti Teknologi Malaysia).

      [40] Berry, M., & Jeffery, R. (2000). An instrument for assessing software measurement programs. Empirical Software Engineering, 5(3), 183-200.

      [41] Beecham, S., Hall, T., Britton, C., Cottee, M., & Rainer, A. (2005). Using an expert panel to validate a requirements process improvement model. Journal of Systems and Software, 76(3), 251-275.

      [42] The Telegrapgh. URL http://www.telegraph.co.uk/finance/newsbysector/mediatechnologyandtelecoms/digital-media/11597743/Teenagers-spend-27-hours-a-week-online-how-internet-use-has-ballooned-in-the-last-decade.html. (visited on 06/02/2016).

      [43] HostingFacts.com. URL https://hostingfacts.com/internet-facts-stats-2016/. (visited on 02/20/2017).

      [44] Ahmad, R., Mahmod, M., Chit, S. C., Na’in, N., Habbal, A., & Wiwied, V. (2017). More Than Money Matters: Examining Motivational Factors for Participating in Crowdsourcing Platform. Advanced Science Letters, 23(5), 4310-4313.

      [45] Aitamurto, T. (2015). Motivation factors in crowdsourced journalism: Social impact, social change, and peer learning. URL http://ijoc.org/index.php/ijoc/article/download/3481/1502. (visited on 08/08/2016).

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  • How to Cite

    Solemon, B., & Abu Bakar, W. M. L. W. (2018). Factors Motivating the Public to Participate in Crowdsourcing of Crime Information. International Journal of Engineering & Technology, 7(4.35), 583-588. https://doi.org/10.14419/ijet.v7i4.35.22917

    Received date: 2018-12-02

    Accepted date: 2018-12-02

    Published date: 2018-11-30