Abstract
The evolutionary history of the human brain shows advancement in its complexity and creativity during its evolutionary path from early primates to hominids, and finally to Homo sapiens. This most powerful human asset known as the brain is highly capable of solving problems. When a problem arises, humans make use of their intelligence and various methods of finding the solution. No doubt they have come up with the best solutions, but many questions have been raised on how that problem is approached and how the solution is derived. The peculiar thing is that everyone has a different mechanism of thinking and comes up with different patterns of solutions. Can this pattern be mimicked by a machine where a problem can be solved by inputs from multiple individuals? Crowdsourcing and neural networks come into play in this domain. Crowdsourcing deals with the pooling of ideas by people. The more people, the wider the perspective obtained. The data given by them are processed and the field of neural networks plays a vital role in analyzing the data. These data contain various patterns and hidden solutions to many problems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ambani, P.: Crowdsourcing new tools to start lean and succeed in entrepreneurship: entrepreneurship in the crowd economy. Crowdfunding Sustain. Entrep. Innov. 37 (2016)
Atlas, D., Çilingirirturk, A.M., Gulpinar, V.: Analyzing the process of the artificial neural networks by the help of the social network analysis, pp. 80–91 (2013)
Biella, D., Sacher, D., Weyers, B., Luther, W., Baloian, N., Schreck, T.: Crowdsourcing and knowledge co-creation in virtual museums. In: CYTED-RITOS International Workshop on Groupware, pp. 1–18. Springer International Publishing, Berlin (2015)
Bongard, J.C., et al.: Crowdsourcing predictors of behavioral outcomes. IEEE Trans. Syst. Man Cybern. Syst. Hum. 43(1), 176–185 (2013)
Doan, A., Ramakrishnan, R., Halevy, A.Y.: Crowdsourcing systems on the world-wide web. Commun. ACM 54(4), 86–96 (2011)
Dragoni, M.M.N., Marrafa, L.B.A., de Nicola, S.: Social networks and collective intelligence: a return to the Agora. Soc. Netw. Eng. Secure Web Data Serv. 88 (2013)
Gellers, J.C.: Crowdsourcing sustainable development goals from global civil society: a content analysis (2015)
Howe, J.: The rise of crowdsourcing. Wired Magazine. Accessed at https://www.wired.com/2006/06/crowds/ (2006). Accessed Nov 2016
Li, J., et al.: Learning from the crowd with neural network. In: 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA). IEEE, New York (2015)
Melin, P., Castillo, O., Kacprzyk, J. (eds.) Nature-Inspired Design of Hybrid Intelligent Systems, vol. 667. Springer, Berlin (2016)
Peng, X., Babar, M.A., Ebert, C.: Collaborative software development platforms for crowdsourcing. IEEE Softw. 31(2), 30–36 (2014)
Schimak, G., Havlik, D., Pielorz, J.: Crowdsourcing in crisis and disaster management—challenges and considerations. In: International Symposium on Environmental Software Systems. Springer International Publishing, Berlin (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Sharma, S., Kumar, H. (2017). Extensible Platform of Crowdsourcing on Social Networking Sites: An Analysis. In: Banati, H., Bhattacharyya, S., Mani, A., Köppen, M. (eds) Hybrid Intelligence for Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-65139-2_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-65139-2_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-65138-5
Online ISBN: 978-3-319-65139-2
eBook Packages: Computer ScienceComputer Science (R0)