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Big Data techniques applied to stakeholder data for non-governmental organizations

Abstract:

Non-governmental organizations, foundations, and various social actors promote the mobilization of the sustainable development goals set by the United Nations and contribute to improving the population's quality of life. Frequently, the search for opportunities to generate agreements and social innovation projects is done manually by accessing the web and selecting, according to the search, those calls that best align with the interests of each social actor. These activities are performed repeatedly by one person spending a lot of time, affecting productivity and timeliness in finding and implementing the social partnerships. Considering the technological advances and known Big Data techniques, an opportunity is identified to improve the results of these activities by automating the operations. This paper presents an alternative to optimize the searching and segmentation of possible projects. Through the implementation of web scraping techniques according to keywords in social topics and clustering algorithms for the creation of groups of initiatives according to similar features, to generate partnerships between actors and social calls, which ultimately impact the generation of alliances and networks with a common cause, benefiting more communities.