Resilient reporting: Media coverage of Irish elections since 1969 - Hardcover

Breen, Michael; Courtney, Michael; Mcmenamin, Iain

9781526119971: Resilient reporting: Media coverage of Irish elections since 1969

Hardcover

ISBN 10: 1526119978 ISBN 13: 9781526119971

Verlag: Manchester University Press, 2019

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This timely book examines how election news reporting has changed over the last half-century in Ireland, by analysing reporting in terms of framing, tone, and the distribution of coverage.

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Kevin Rafter is head of the department of film and media at the Institute of Art, Design and Technology, Dun Laoghaire.

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Media hostility towards politicians and the political system, and its impact on democracy, has long attracted the interest of scholars of political communication. It is also the subject of political discourse and rhetoric, with the media attracting the ire of political leaders around the globe: Donald Trump, for one, has repeatedly called journalists 'the worst people in the world.' Trump is not the first, nor will he be the last, leader to seek to focus our attention on the role of the media in electoral politics.

Resilient reporting examines how election news reporting has changed over the last half-century in Ireland by means of a unique dataset involving 25 million words from newspapers, as well as radio and television coverage. In a timely and revealing study, the authors examine reporting in terms of framing, tone, and the distribution of coverage. They also focus on how the economy has affected election coverage as well as media reporting of leaders and personalities, gender, and the effect of the commercial basis of media outlets.

The authors evaluate three broad hypotheses about Ireland’s election coverage since 1969: the extent to which the norms of critical impartiality have survived, whether the media has shifted towards hypercritical infotainment, and the extent to which content has been influenced by exogenous factors — that is, political, social, and economic factors outside the media itself.

The findings, which are drawn from a machine-learning computer system involving a huge content analysis study, will interest academics as well as politicians and policymakers internationally.

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