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Social media as a political backchannel: Twitter use during televised election debates in Norway
Purpose - The purpose of this paper is to explore how Twitter is used as a political backchannel and potential agenda setter during two televised political debates during the Norwegian election in 2011. The paper engages with current debates about the role of social media in audience participation a...
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Published in: | Aslib journal of information management 2014-01, Vol.66 (3), p.313-328 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Purpose - The purpose of this paper is to explore how Twitter is used as a political backchannel and potential agenda setter during two televised political debates during the Norwegian election in 2011. The paper engages with current debates about the role of social media in audience participation and traditional media's changing role as gatekeepers and agenda setter. Design/methodology/approach - A combination of quantitative and qualitative methods. By introducing and using the IMSC multiple step analysis model on the Twitter datasets, the authors are able to analyse the flow of thousands of tweets and compare them with topics discussed in the televised debates. Findings - The paper finds that the same topics are discussed on Twitter as on TV, but "the debate about the debate" or Meta talk tweets reveal critical scrutiny of the agenda. The paper identifies a clear pattern of political fandom and media criticism in the "debate about the debate", indicating that Meta talk in social media can function as a critical public sphere, also in real time, which has not been identified in existing studies of Twitter and political TV shows. Originality/value - The analysis is unique in the sense that the paper analyses a smaller, national Twitter population in deeper detail than what is common in larger Twitter studies related to political televised debates. The IMSC model can be used in future Twitter studies to uncover layers in the data material and structure the findings. |
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ISSN: | 2050-3806 0001-253X |
DOI: | 10.1108/AJIM-09-2013-0093 |