The value of social media data: Integrating crowd capabilities in evidence-based policy

Panagiotopoulos, Panos, Bowen, Frances and Brooker, Phillip (2017) The value of social media data: Integrating crowd capabilities in evidence-based policy. Government Information Quarterly, 34 (4). pp. 601-612. ISSN 0740-624X

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Social media have been widely embraced by governments for information dissemination and engagement but less is known about their value as information sources. Crowdsourced content from social media can improve inclusivity in policy development but it is not always clear how it can form part of policy evidence. The paper builds on the conceptual framework of crowd capabilities to examine the value of social media data in evidence-based policy. Acquisition and assimilation – the two elements of crowd capabilities – drive our exploratory case analysis in the context of agricultural policies in the UK. The study combined qualitative data from interviews and workshops with an analysis of networks of farmers on Twitter. Policy makers were broadly positive about the immediacy, cost-effectiveness and diversity of useful input that can be sourced from online sources. Limitations were identified in terms of representation and inclusion of participants in large datasets that are sourced from open platforms. We compare social media data to traditional sources of evidence and further reflect on the new capabilities that can support the needs of policy makers in this endeavor.

Item Type: Article
Uncontrolled Keywords: absorptive capacity,big data,case study,environment and farming,policy crowdsourcing,sociology and political science,library and information sciences,law ,/dk/atira/pure/subjectarea/asjc/3300/3312
Faculty \ School: Faculty of Social Sciences > Norwich Business School
UEA Research Groups: Faculty of Social Sciences > Research Centres > Centre for Competition Policy
Faculty of Social Sciences > Research Groups > Responsible Business Regulation Group
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Depositing User: LivePure Connector
Date Deposited: 30 May 2019 15:30
Last Modified: 12 May 2023 22:30
DOI: 10.1016/j.giq.2017.10.009

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