Ethnic’ media and election campaigns
Chinese and Indian media in New Zealand’s 2017 election
Bibliographic Data
| ID | 6234576 |
|---|---|
| Authors | Kate Mcmillan (0000-0003-1408-2994, Political Science and International Relations, Victoria University of Wellington, Wellington, New Zealand, corresponding author), Fiona Barker (0000-0002-7856-2922, Political Science and International Relations, Victoria University of Wellington, Wellington, New Zealand) |
| Year | 2021 |
| Volume | 56 |
| Issue | 2 |
| Pages | 113-131 |
| Publication date | 2021-04-03 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Australian Journal of Political Science (JOURNAL) |
| Journal identifiers | ISSN: 1036-1146 • E-ISSN: 1363-030X |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10361146.2021.1884644 |
| OpenAlex | W3134246729 |
| Language | EN |
| Citations received | 7 |
| References cited | 14 |
This article provides the first systematic study of the political content of New Zealand's Chinese and Indian print and online news media during an election campaign period. We assess the comprehensiveness and political balance of election coverage provided by a sample of high-circulation New Zealand-based Chinese and Indian news publications during New Zealand's 2017 campaign. Overall, we find all the publications in our sample under-reported minor parties and, in some cases, the quantity and tone of their reporting demonstrated strong bias towards the National Party. These findings are significant in a context where such media play an important role in informing ethnic and immigrant minorities during campaigns, and where such minorities form a growing proportion of the New Zealand electorate
Context (archaeology · Ethnic group · General election · Geography · Immigration · Political science · Politics · Sample (material · Tone (literature · Law · Media Studies and Communication · Migration, Refugees, and Integration · Social Media and Politics
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| Unique citing works | 7 |
|---|---|
| Citations per year | 1,4 |
| Citation span | 2021 - 2025 (5) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |