Analysis on Potential Use of Crowdsourcing in Different Domain Using Metasynthesis

Kasturi, Nivedita; Totad, S. G.; Ghosh, Goldina

doi:10.1007/978-981-19-4193-1_73

Cited by 2 publications

(2 citation statements)

References 35 publications

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“…In the crowdsourcing era, in its early days, it has been preliminarily defined as a problem-solving model [3], and recently, it has been reviewed in a wide range of domains [4]; software engineering, in between, has gained a considerable share in this emerging field [5], [6]. The notion of a problem-solving model for crowdsourcing is suggested by [3] for various applications while providing model examples and denoting contentious points such as crowds diversity, crowds exploitations, and intellectual labor, as well as other topics.…”

Section: Introductionmentioning

confidence: 99%

“…The notion of a problem-solving model for crowdsourcing is suggested by [3] for various applications while providing model examples and denoting contentious points such as crowds diversity, crowds exploitations, and intellectual labor, as well as other topics. A recent comprehensive literature review of all various fields where crowdsourcing has been utilized is authored by [4], which is the first literature to investigate all possible domains related to crowdsourcing. As crowdsourcing has been adopted in various domains, it has become an important topic.…”

Section: Introductionmentioning

confidence: 99%

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A Review of Trending Crowdsourcing Topics in Software Engineering Highlighting Mobile Crowdsourcing and AI Utilization

Alghasham¹,

Alzakan²,

Al-Hagery³

2023

IJACSA

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Today's modern technologies and requirements make the utilization of crowdsourcing more viable and applicable. It is one of the problem-solving models that can be used in various domains to reduce costs and time. It is also an excellent way to find new and different ideas and solutions. This paper studies the use of crowdsourcing in software engineering and reveals adequate details to highlight its significance. A few recent literature reviews have been published to address specific topics or study general attributes of papers in crowdsourced software engineering. This paper, however, explores all recent publications related to software and crowdsourcing to find the trends and highlight mobile and AI usage in software crowdsourcing. The findings of this paper show that most research papers are in the areas of software management and software verification and validation. The results also reveal that machine learning and data mining techniques are predominant in software management crowdsourcing and software verification and validation. Furthermore, this study shows that the methods and techniques used in general crowdsourcing apply to mobile crowdsourcing except in mobile testing, where there is a need for clustering and prioritization of test reports.

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