Wikipedia: The Concept of Data-Driven Crowdsourcing

At the beginning of its conception, the Internet was a poorly organized set of websites and pieces of knowledge that was scattered across the network. However, as the Internet became an integral part of millions of people’s lives, the necessity to collect, arrange, store, and share data properly emerged. Thus, Wikipedia as the global repository of knowledge in all areas emerged. However, being a nonprofit organization, Wikipedia needs additional sources of support to remain sustainable and continue to provide the required services to its target audiences. Herein lies the significance of crowdsourcing as the platform based on which Wikipedia can function. By utilizing crowdsourcing as the guiding principle for the company to operate and provides articles regularly, the Wikipedia leaders both open opportunities for creating quality content and face new threats regarding the lack of control over the process. The specified concerns are essential attributes of crowdsourcing, yet they can be controlled by establishing a set of rigid principles based on which corporate processes occur.

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When considering the changes that Wikipedia has experienced, as well as the principles based on which it is run, one will have to recognize the importance of crowd wisdom as the cornerstone of the site’s existence. Although the suggested tool does not guarantee to complete expertise and a profound understanding of a particular subject by contributors, it does create the platform for Wikipedia to continue its progress. The site represents the combined experience of millions of people and, thus provides extensive opportunities for an objective overview of a range of problems, concepts, and phenomena. Furthermore, the specified framework contributes to the rise in diversity levels within the site and opens a cross-cultural dialogue.1 Viewing a certain issue from the perspective of diverse experiences enables one to delve into the nature of the problem and contribute to the expansion of the global knowledge system. Therefore, the choices made by the Wikipedia owner seem legitimate, yet further adjustments are required to retain the corporate integrity and promote the relevant values to Wikipedia’s contributors.

It should be noted that there are several disadvantages to selecting crowdsourcing as the primary tool for handling essential production-related and organizational processes within a company. The lack of control over the choices made by the crowd can be seen as the most problematic aspect of crowdsourcing. Indeed, it is rather difficult to ensure that people do not overstep the set boundaries and add information that is unverified, biased, or simply incorrect. The instances of adding the data that does not reflect the existing situation objectively are known among Wikipedia members; particularly, there is a term for the specified phenomenon. The pages that have undergone massive unverified changes and have been affected by people negatively are termed as vandalized.2 As a result, the information represented at Wikipedia is not considered credible despite the vast range of qualified experts that have contributed to it, and the site cannot currently be deemed as appropriate for academic referencing.

Nonetheless, the specified issue can be addressed by bringing order to the ranks of Wikipedia’s contributors and ensuring that its guests behave according to the set guidelines. The process of organizing a crowd is rather lengthy and painstaking, yet it has a profound and positive effect on the overall management of an organization, as the case of Wikipedia has shown.3 The rise in the popularity of the site and the focus on the independence of contributors have led to the successful management of the information and arrangement of roles within the company.4 Specifically, the contributors to the site have set elaborate standards for introducing new information to the site and creating new pages, as well as adding data to the existing ones and correcting it. As a result, the site is run adequately, with its members handling the continuous flow of data effectively and making it the place where millions of people come to acquire new knowledge.5 The Wikipedia community has become the platform for the company’s growth due to the geeky leadership system and the passion of the people involved in the project.

The idea of crowdsourcing might seem like a rather dubious choice when it comes to managing essential processes within an organization, yet the example of Wikipedia shows that the specified method works once utilized properly. With a clear focus on the relevant values, as well as the creation of the culture of geeky leadership, Wikipedia has managed to not only survive but also strive. The stunning success that the site has witnessed should be attributed to its community and the efforts of its contributors, which signifies the importance of using crowdsourcing right. Wikipedia manages its information systems properly, yet the lack of control over the actions of its contributors introduces the element of risk into its functioning. Nonetheless, the key operations within the system can be regulated successfully by reinforcing the principles of ethics based on which the site operates. The suggested step will create the basis for the site contributors to focus on supervising compliance with the existing standards and principles that users have set, as well as updating these rules to meet new quality demands.


Afuah, A. (2014). Business model innovation: Concepts, analysis, and cases. New York, NY: Routledge.

Chen, L., Lee, D., & Milo, T. (2015, April). Data-driven crowdsourcing: Management, mining, and applications. In Data engineering (ICDE), 2015 IEEE 31st International Conference (pp. 1527-1529). Piscataway, NJ: IEEE.

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Jetha, M. (2018). MAN6830: Week 4 – Core and crowd [Video file]. Web.

Li, G., Wang, J., Zheng, Y., & Franklin, M. J. (2016). Crowdsourced data management: A survey. IEEE Transactions on Knowledge and Data Engineering, 28(9), 2296-2319.

Yang, D., Halfaker, A., Kraut, R. E., & Hovy, E. H. (2016, March). Who did what: Editor role identification in Wikipedia. In ICWSM (pp. 446-455). Menlo Park, CA: AAAI Press.


  1. Jetha, 2018.
  2. Yang, Halfaker, Kraut, & Hovy, 2016.
  3. Afuah, 2014.
  4. Li, Wang, Zheng, & Franklin, 2016.
  5. Chen, Lee, & Milo, 2015.
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StudyCorgi. "Wikipedia: The Concept of Data-Driven Crowdsourcing." June 23, 2021.


StudyCorgi. 2021. "Wikipedia: The Concept of Data-Driven Crowdsourcing." June 23, 2021.


StudyCorgi. (2021) 'Wikipedia: The Concept of Data-Driven Crowdsourcing'. 23 June.

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