Media Context and the 2017 General Election: How Traditional and Social Media Shape Elections

DOI

Abstract copyright UK Data Service and data collection copyright owner.

The Media Context and the 2017 General Election: How Traditional and Social Media Shape Elections data consist of an analysis of media coverage of the 2017 British General Election. Media included are national newspapers, local newspapers, national and regional television news, and radio. The complete list of outlets is included in the codebooks. This study was conducted as part of the ESRC Media in Context and the 2017 General Election award, which extends the analysis of the 2015 election, data available under SN 8176.In 2017 the electoral context had shifted from two years earlier, with a majority Conservative government, different leaders of almost all the major parties, Brexit as both the main issue (prior to the terrorist bomb in Manchester) and the ostensible reason the election was called, the possibility of the incumbent government gaining the largest proportion of the vote in a generation, and a growing distrust of polling data and the media e.g., ‘fake news’ and Twitter bots. This provided us with the opportunity to re-examine media coverage and extend our aims in four ways, by: 1) Looking at media coverage and its effects on different leaders and different issues than in 2015, e.g., Theresa May, Jeremy Corbyn, and Brexit; 2) Comparing the drivers of coverage of the election in traditional and social media, how they interact, and their effects in an era of “fake news” and “post-truth democracy” ; 3) Drawing links between key narratives in the 2015 post-election media coverage that led to the EU referendum and key narratives on Brexit in the 2017 campaign; 4)Identifying the aspects of media and media effects that vary between a competitive and an uncompetitive election at the national level and those that stay constant. Data collection was for the following additional objectives: 1. To extend the longitudinal data set using the methods we established for the 2015 media content, capturing traditional and social media coverage of the 2017 election beginning on April 18th, 2017, the day Theresa May announced her intention to call an election and ending with the Queen’s speech on June 21st. 2. As in ES/M010775/1, to link traditional media content and social media analysis from 2017 to questions in the British Election Study, both allowing examination of media effects in 2017, and, for the same respondents, in 2015 for comparison.Further information about this study can be found on the Gateway to Research webpages.

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The media data were collected through Box of Broadcasts (TV and Radio) and Nexis (newspapers).

The Twitter data were collected through the Twitter streaming API between 18 April 2017 and 8 June 2017, using the following keywords: ge2017, corbyn, may, sturgeon, labour, conservative, tory, election, ukip, libdem, plaid, snp, green party, debate, mp, candidate, constituency, parliament, westminster, whitehall, vote, voting, ballot, poll, turnout, manifesto, cabinet, ukpolitics.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-8397-1
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=5a66f6826cbd0b0ce8234704faf0f5c1ea2501c0ab9a21b50587e5b28351aec3
Provenance
Creator Cioroianu, I., University of Exeter, Centre for Elections, Media and Participation; Banducci, S., University of Exeter; Coan, T., University of Exeter, Centre for Elections, Media and Participation; Stevens, D., University of Exeter, Centre for Elections, Media and Participation
Publisher UK Data Service
Publication Year 2018
Rights Copyright D. Stevens, S.A. Banducci and T. Coan<br>; <p>The Data Collection is available to UK Data Service registered users subject to the <a href="https://ukdataservice.ac.uk/app/uploads/cd137-enduserlicence.pdf" target="_blank">End User Licence Agreement</a>.</p><p>Commercial use of the data requires approval from the data owner or their nominee. The UK Data Service will contact you.</p>
OpenAccess true
Representation
Resource Type Numeric
Discipline Social Sciences
Spatial Coverage United Kingdom