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Chances and Challenges of Computational Data Gathering and Analysis : The case of issue-attention cycles on Facebook

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Author(s)
Sormanen, Niina
Rohila, Jukka
Lauk, Epp
Uskali, Turo
Jouhki, Jukka
Penttinen, Maija
Keywords
computational data gathering
data warehouse
digital and social media research
Facebook
hybrid news ecosystem
issue-attention cycle
news flows
semi-public data
518, 113

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URI
http://hdl.handle.net/20.500.12424/3750318
Online Access
http://urn.fi/URN:NBN:fi:jyu-201601121093
Abstract
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.
Date
2016-01-13
Type
Article
Identifier
oai:jyx.jyu.fi:123456789/48335
URN:NBN:fi:jyu-201601121093
http://urn.fi/URN:NBN:fi:jyu-201601121093
Copyright/License
openAccess
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