Chances and Challenges of Computational Data Gathering and Analysis : The case of issue-attention cycles on Facebook
Sormanen, N., Rohila, J., Lauk, E., Uskali, T., Jouhki, J., & Penttinen, M. (2016). Chances and Challenges of Computational Data Gathering and Analysis : The case of issue-attention cycles on Facebook. Digital Journalism, 4 (1), 55-74. doi:10.1080/21670811.2015.1096614
Published inDigital Journalism
© 2015 Taylor & Francis. This is a final draft version of an article whose final and definitive form has been published by Taylor & Francis. Published in this repository with the kind permission of the publisher.
Digital and social media and large available data-sets generate various new possibilities and challenges for conducting 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 analysing 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 demonstrated method can be used for gathering and analysing large sets of data from various social network sites and national contexts. The paper also discusses Facebook platform regulations concerning data gathering and ethical issues in conducting online research.