People as sensors: Mass media and local temperature influence climate change discussion on Twitter

被引:118
作者
Kirilenko, Andrei P. [1 ]
Molodtsova, Tatiana [1 ]
Stepchenkova, Svetlana O. [2 ]
机构
[1] Univ N Dakota, Dept Earth Syst Sci & Policy, Grand Forks, ND 58202 USA
[2] Univ Florida, Dept Tourism Recreat & Sport Management, Gainesville, FL 32611 USA
来源
GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS | 2015年 / 30卷
关键词
Climate change; Temperature; Social media; Twitter; Mass media; PUBLIC PERCEPTIONS; UNITED-STATES; CITIZENS;
D O I
10.1016/j.gloenvcha.2014.11.003
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study examined whether people living in the US connect their sensory experiences with local temperature to climate change and whether mass media influences the process. We used the volume of Twitter messages containing words "climate change" and "global warming" as the indicator of attention that public pays to the issue. Specifically, the goals were: (1) to investigate whether people immediately notice substantial local weather anomalies such as deviations from long-term mean temperatures and connect them to climate change by contributing to climate change discourse on Twitter and (2) to examine the role of mass media in this process. Over 2 million tweets were collected for a two-year period (2012-2013) and were assigned to 157 urban areas in the continental US. The rate of tweeting on climate change was regressed on the time variables, number of climate change publications in the mass media, and a number of temperature variables. The analysis was conducted at the two levels of aggregation - national and local. The high significance of the mass media and temperature variables in the majority of regression models suggests that both the weather and mass media coverage control public interest to the topic. However, no convincing evidence was found that the media acts as a mediator in the relationship between local weather and climate change discourse. Overall, the findings confirmed that the public recognize extreme temperature anomalies and connect these anomalies to climate change. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:92 / 100
页数:9
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