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Cited by 418

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Telling Stories About Global Climate Change: Measuring the Impact of Narratives on Issue Cycles

McCOMAS, KATHERINE, SHANAHAN, JAMES·1999·Communication Research

Abstract

A theory of cyclical patterns in media coverage of environmental issues must account for more than intrinsic qualities of the issues themselves: Narrative factors must be considered. A content analysis of The New York Times and The Washington Post stories from 1980 to 1995 shows how media construct narratives about global warming and how these narratives may influence attention cycles. Empirically, the frequency of newspaper coverage shows cyclical attention to global warming. The content analysis further reveals that implied danger and consequences of global warming gain more prominence on the upswing of newspaper attention, whereas controversy among scientists receives greater attention in the maintenance phase. The economics of dealing with global warming also receive greater attention during the maintenance and downside of the attention cycle. The discussion offers a narrative explanation and suggests the outcome of the “master story” of global climate change may discourage future attention to global warming.

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Metadata

Authors
McCOMAS, K., & SHANAHAN, J.
Venue
Communication Research
Published
1999-02
Volume
26
Issue
1
Pages
30-57
ISSN
  • 0093-6502 (ISSN-L)
  • 1552-3810
OpenAlex
W2152810040
Cited by
418
References
3
FWCI
12.82
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Telling Stories About Global Climate Change: Measuring the Impact of Narratives on Issue Cycles. https://app.cochat.ai/papers/10.1177/009365099026001003
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McCOMAS, K., & SHANAHAN, J. (1999). Telling Stories About Global Climate Change: Measuring the Impact of Narratives on Issue Cycles. Communication Research. https://doi.org/10.1177/009365099026001003

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.