Innovation in sociology

Scholarly attitudes towards innovative research methods in the intersection of social and computational sciences

Abstract

The digitization of society requires science to develop in a way that promotes interdisciplinary collaboration between social sciences and data science. Although social scientists are increasingly open to using the methods of computational social science and social computing, there are hardly any examples of projects implemented as a collaboration between social science and data science and which focus on the evaluation and development of data collection, analysis, and dissemination methods. We used a mixed methodology in our exploratory research: we assessed the willingness of social scientists and data scientists to use various research methods and tools by means of an online questionnaire, then explored scientists' attitudes towards innovative social research methods during interviews. Our findings confirm the importance of interdisciplinary collaboration and highlight the significance of the role of 'interpreters' able to communicate with and connect various areas of science. In terms of research methodology, the findings also highlight concerns related to the validity and credibility of data, and identify the practice of open science, the sharing of data and research methodologies and the transparency of research as key to the development of social science.