This article analyzes the ethical discussion focusing on the Facebook emotional contagion experiment published by the <em>Proceedings of the National Academy of Sciences</em> in 2014. The massive-scale experiment manipulated the News Feeds of a large amount of Facebook users and was successful in proving that emotional contagion happens also in online environments. However, the experiment caused ethical concerns within and outside academia mainly for two intertwined reasons, the first revolving around the idea of research as manipulation, and the second focusing on the problematic definition of informed consent. The article concurs with recent research that the era of social media and big data research are posing a significant challenge to research ethics, the practice and views of which are grounded in the pre social media era, and reflect the classical ethical stances of utilitarianism and deontology.

Words count: Core text (Title-References) 7677, Tables and Figure captions 1099. Digital and social media and large available data sets generate various new possibilities and challenges for doing research focused on perpetually developing online news ecosystems. This paper presents a novel computational technique for gathering and processing large quantities of data from Facebook. We demonstrate how to use this technique for detecting and analyzing issue-attention cycles and news flows in Facebook groups and pages. Although the paper concentrates on a Finnish Facebook group as a case study, the method demonstrated can be used for gathering and analyzing large sets of data from various social network sites and national contexts. The paper also discusses Facebook platform regulations of data gathering and ethical issues of doing online research.

No abstract