Linking Local Weather To Climate Change: One Year Of Twitter In The US

There is a high level of scientific consensus on climate change. Nevertheless for climate change research to have any practical value, to develop public support for climate policies, the climate research results must find the way to general public. That is why it is important to understand how the public perception of climate change forms. During the last decades there have been a number of studies on the factors affecting the level of public concern on climate change. Two major groups of factors are hypothesized to have the biggest influence on the level of public concern on climate change: extreme weather events and the mass media topic coverage. Local studies confirm that the weather events experienced by people in certain locations might be related to climate change. In 1998 James Hansen hypothesized that two weather parameters\u27 variations, namely, temperature and precipitation, exceeding one standard deviation should be noticeable by people and result in increase of the level of public concern on the phenomena. Nevertheless no previous studies were able to test this hypothesis and demonstrate that people truly use the information about local weather to make assumptions about climate change. The other studies on public perception of climate change are generally based on the agenda-setting theory, stating that the level of public concern on the issue is a reflection of the extent and prominence of media coverage of the topic. The previous studies on how public perception of climate change forms are mainly based surveys, which is an active approach to collect social data. With the development of social media, however, a passive surveying of public perceptions on climate change has become possible. In this thesis the change in climate change microblogging intensity in Twitter was used as a proxy of change in the level of concern on the issue. The objectives of the study were to utilize the Twitter, a currently the most popular microblogging platform, as a source of public salience data to test if the changes in weather parameters and in media coverage result in changes of the level of public concern on climate change. For this purpose the multiple linear regression and multi-model inference statistical techniques were used on three geographical levels of data aggregation. The results clearly show that changes in weather parameters have significant effect on the level of public concern on climate change on the national, regional and local scales. The mass media topic coverage was also positively associated with the level of public concern on the national level. The study demonstrated that the social media data provides unprecedented opportunities for public opinion research