7th Biennial ACSPRI Social Science Methodology Conference

Regina Lenart-Gansiniec

Prof. Dr. Regina Lenart-Gansiniec is Associate Professor in the Institute of Public Affairs, Jagiellonian University, Krakow, Poland. Her research focuses on open innovation, crowdsourcing, crowdfunding, knowledge management, and organizational learning in public organizations. She is an author of publications on knowledge management, crowdsourcing and open innovation.


Crowdsourcing in social science research: a systematic review

In recent years, governments in many countries have implemented higher education reforms. Their goal was to provide more freedom to universities, to improve the quality of higher education and to professionalize the work of academic workers. Academics are expected to include members of the public in research projects, to establish cooperation with scientists from other research centers and to increase the quality of research. In this context, the scientific enterprise is built on a foundation of trust. Society trusts that scientific research results are an honest and accurate reflection of a researcher's work. Researchers equally trust that their colleagues have gathered data carefully, have used appropriate analytic and statistical techniques, have reported their results accurately, and have treated the work of other researchers with respect.
Scientific crowdsourcing has become an important part of the changing science landscape. Scientific crowdsourcing is a new way of contemporary scientific research activities, an example of opening of science and research, an alternative to research projects, a strategy for organising the work of a researchers (Lukyanenko, Parsons, Wiersma, & Maddah, 2019) and tool for research (Law, Gajos, Wiggins, Gray, & Williams, 2017). Scientific crowdsourcing enables new collaborative forms of knowledge creation, scientific crowdsourcing is an online content creation tool (Doan, Ramakrishnan, & Halevy, 2011) communicating academic teachers with each other and with people from outside the scientific community, collecting or classifying data (Beck, Brasseur, Poetz, & Sauermann, 2019). It is also the practice of obtaining participants, services, ideas, or content by soliciting contributions from a large group of people, especially via the Internet (Brown & Allison, 2014).
Scientific crowdsourcing facilitates the process of collecting, processing and analysing research data (Law et al., 2017), enlisting participants for surveys, research, experiments, panels, focus groups, statistical analyses, transcriptions (Schlagwein & Daneshgar, 2014), generating innovative research questions, hypotheses, research proposals, testing research at an early stage. Scientific crowdsourcing also allows you to reduce costs of conducting research, to provide the researchers involved with funding, to establish cooperation and to seek collaborators for joint research, to obtain assessment and opinions (Uhlmann et al., 2019) on the concept of a given research project or an article, to solve problems arising in the course of writing an article or conducting research (Hevner, March, Park, & Ram, 2013), to determine the reliability and generalisation of the results and to disseminate the results (Beck et al., 2019). The purpose of this systematic review is to summarize quantitative evidence on use of crowdsourcing in social science research. We screened 86 articles.