Ethical Issues in Social Science Research Employing Big Data

Abstract

This paper analyzes the ethics of social science research (SSR) employing big data. We begin by highlighting the research gap found on the intersection between big data ethics, SSR and research ethics. We then discuss three aspects of big data SSR which make it warrant special attention from a research ethics angle: (1) the interpretative character of both SSR and big data, (2) complexities of anticipating and managing risks in publication and reuse of big data SSR, and (3) the paucity of regulatory oversight and ethical recommendations on protecting individual subjects as well as societies when conducting big data SSR. Against this backdrop, we propose using David Resnik’s research ethics framework to analyze some of the most pressing ethical issues of big data SSR. Focusing on the principles of honesty, carefulness, openness, efficiency, respect for subjects, and social responsibility, we discuss three clusters of ethical issues: those related to methodological biases and personal prejudices, those connected to risks arising from data availability and reuse, and those leading to individual and social harms. Finally, we advance considerations to observe in developing future ethical guidelines about big data SSR.

Network analysis in peace and state building: revealing power elites

“…Maintaining ethical standards in data science tools is crucial, necessitating the mitigation of risks related to data publication and reuse (Cai and Zhu, 2015; Hosseini et al, 2022). For instance, when governments or powerful entities utilize analytical tools and AI, there’s a risk of leveraging their authority to control data repositories.…”

Ethical Considerations in Data Collection and Analysis: A Review: Investigating Ethical Practices and Challenges in Modern Data Collection and Analysis

“…This perspective underscores the need for researchers to be cognizant of the ethical implications of their work from the outset, ensuring that their methodologies and analyses adhere to established ethical norms. Hosseini, Wieczorek, and Gordijn (2022) delve into the ethical issues specific to social science research employing big data. They identify unique challenges in this domain, such as the interpretative nature of social science and big data, complexities in managing risks in publication and reuse of big data, and the lack of regulatory oversight.…”

“…This study underscores the need for ethical frameworks that can mitigate the negative implications of Big Data and AI, ensuring that digital media contributes positively to democratic processes and the well-being of citizens. Hosseini, Wieczorek, and Gordijn (2022) delve into the ethical issues specific to social science research employing big data. They identify unique challenges such as the interpretative nature of social science and big data, complexities in managing risks in publication and reuse, and the lack of regulatory oversight.…”

“…Bridging the research gap in data ethics is essential for ensuring responsible and ethical use of data in various fields. Hosseini, Wieczorek, and Gordijn (2022) address the ethical issues in social science research employing big data, highlighting the intersection between big data ethics, social science research, and research ethics. They emphasize the interpretative character of both social science and big data, the complexities of managing risks in publication and reuse, and the lack of regulatory oversight.…”

Data and science engineering: The ethical dilemma of our time-exploring privacy breaches, algorithmic biases, and the need for transparency

“…These impacts include, loss of Trust Privacy breaches, algorithmic bias, and the lack of transparency can all lead to a loss of trust in data and science engineering technologies. This can make it more challenging for organizations to use these technologies effectively, as individuals may be reluctant to share their data or participate in data-driven decision-making processes [15].…”