Climate Change Communication in an Online Q&A Community: A Case Study of Quora

Hanchen Jiang, Maoshan Qiang, Dongcheng Zhang, Qi Wen, Bingqing Xia and Nan An
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Hanchen Jiang: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Maoshan Qiang: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Dongcheng Zhang: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Qi Wen: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Bingqing Xia: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Nan An: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China

Sustainability, 2018, vol. 10, issue 5, 1-17

Abstract: An emerging research trend in climate change studies is to use user-generated-data collected from social media to investigate the public opinion and science communication of climate change issues. This study collected data from the social Q&A website Quora to explore the key factors influencing the public preferences in climate change knowledge and opinions. Using web crawler, topic modeling, and count data regression modeling, this study quantitatively analyzed the effects of an answer’s textual and auxiliary features on the number of up-votes received by the answer. Compared with previous studies based on open-ended surveys of citizens, the topic modeling result indicates that Quora users are more likely to talk about the energy, human and societal issues, and scientific research rather than the natural phenomena of climate change. The regression modeling results show that: (i) answers with more emphasis on specific subjects, but not popular knowledge, about climate change can get significantly more up-votes; (ii) answers with more terms of daily dialogue will get significantly fewer up-votes; and (iii) answers written by an author with more followers, with a longer text, with more images, or belonging to a question with more followers, can get significantly more up-votes.

Keywords: climate change; science communication; public opinion; social media; topic modeling; regression modeling (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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