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Attention, sentiments and emotions towards emerging climate technologies on Twitter.

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Title: Attention, sentiments and emotions towards emerging climate technologies on Twitter.
Authors: Müller-Hansen, Finn1 (AUTHOR) mueller-hansen@mcc-berlin.net, Repke, Tim1 (AUTHOR), Baum, Chad M.2 (AUTHOR), Brutschin, Elina3 (AUTHOR), Callaghan, Max W.1 (AUTHOR), Debnath, Ramit4,5 (AUTHOR), Lamb, William F.1 (AUTHOR), Low, Sean2 (AUTHOR), Lück, Sarah1 (AUTHOR), Roberts, Cameron6 (AUTHOR), Sovacool, Benjamin K.2,7,8 (AUTHOR), Minx, Jan C.1,9 (AUTHOR)
Source: Global Environmental Change Part A: Human & Policy Dimensions. Dec2023, Vol. 83, pN.PAG-N.PAG. 1p.
Subject Terms: *Environmental engineering, Solar radiation management, Public opinion, Social media, Emotions, User-generated content, Deep learning
Abstract: • We analyze and compare tweets on geoengineering and 16 related climate technologies. • Attention has shifted from general geoengineering to specific carbon removal methods. • Sentiments are more positive for carbon removal than solar radiation management. • Methods perceived closer to nature have the highest shares of positive sentiments. • Our social media analysis is consistent with survey results and qualitative research. Public perception of emerging climate technologies, such as greenhouse gas removal (GGR) and solar radiation management (SRM), will strongly influence their future development and deployment. Studying perceptions of these technologies with traditional survey methods is challenging, because they are largely unknown to the public. Social media data provides a complementary line of evidence by allowing for retrospective analysis of how individuals share their unsolicited opinions. Our large-scale, comparative study of 1.5 million tweets covers 16 GGR and SRM technologies and uses state-of-the-art deep learning models to show how attention, and expressions of sentiment and emotion developed between 2006 and 2021. We find that in recent years, attention has shifted from general geoengineering themes to specific GGR methods. On the other hand, there is little attention to specific SRM technologies and they often coincide with conspiracy narratives. Sentiments and emotions in GGR tweets tend to be more positive, particularly for methods perceived to be natural, but are more negative when framed in the geoengineering context. [ABSTRACT FROM AUTHOR]
Copyright of Global Environmental Change Part A: Human & Policy Dimensions is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: GreenFILE
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Header DbId: 8gh
DbLabel: GreenFILE
An: 173970398
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Attention, sentiments and emotions towards emerging climate technologies on Twitter.
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  Data: <searchLink fieldCode="AR" term="%22Müller-Hansen%2C+Finn%22">Müller-Hansen, Finn</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mueller-hansen@mcc-berlin.net</i><br /><searchLink fieldCode="AR" term="%22Repke%2C+Tim%22">Repke, Tim</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Baum%2C+Chad+M%2E%22">Baum, Chad M.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Brutschin%2C+Elina%22">Brutschin, Elina</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Callaghan%2C+Max+W%2E%22">Callaghan, Max W.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Debnath%2C+Ramit%22">Debnath, Ramit</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lamb%2C+William+F%2E%22">Lamb, William F.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Low%2C+Sean%22">Low, Sean</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lück%2C+Sarah%22">Lück, Sarah</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Roberts%2C+Cameron%22">Roberts, Cameron</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sovacool%2C+Benjamin+K%2E%22">Sovacool, Benjamin K.</searchLink><relatesTo>2,7,8</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Minx%2C+Jan+C%2E%22">Minx, Jan C.</searchLink><relatesTo>1,9</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Global+Environmental+Change+Part+A%3A+Human+%26+Policy+Dimensions%22">Global Environmental Change Part A: Human & Policy Dimensions</searchLink>. Dec2023, Vol. 83, pN.PAG-N.PAG. 1p.
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  Data: *<searchLink fieldCode="DE" term="%22Environmental+engineering%22">Environmental engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Solar+radiation+management%22">Solar radiation management</searchLink><br /><searchLink fieldCode="DE" term="%22Public+opinion%22">Public opinion</searchLink><br /><searchLink fieldCode="DE" term="%22Social+media%22">Social media</searchLink><br /><searchLink fieldCode="DE" term="%22Emotions%22">Emotions</searchLink><br /><searchLink fieldCode="DE" term="%22User-generated+content%22">User-generated content</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: • We analyze and compare tweets on geoengineering and 16 related climate technologies. • Attention has shifted from general geoengineering to specific carbon removal methods. • Sentiments are more positive for carbon removal than solar radiation management. • Methods perceived closer to nature have the highest shares of positive sentiments. • Our social media analysis is consistent with survey results and qualitative research. Public perception of emerging climate technologies, such as greenhouse gas removal (GGR) and solar radiation management (SRM), will strongly influence their future development and deployment. Studying perceptions of these technologies with traditional survey methods is challenging, because they are largely unknown to the public. Social media data provides a complementary line of evidence by allowing for retrospective analysis of how individuals share their unsolicited opinions. Our large-scale, comparative study of 1.5 million tweets covers 16 GGR and SRM technologies and uses state-of-the-art deep learning models to show how attention, and expressions of sentiment and emotion developed between 2006 and 2021. We find that in recent years, attention has shifted from general geoengineering themes to specific GGR methods. On the other hand, there is little attention to specific SRM technologies and they often coincide with conspiracy narratives. Sentiments and emotions in GGR tweets tend to be more positive, particularly for methods perceived to be natural, but are more negative when framed in the geoengineering context. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Global Environmental Change Part A: Human & Policy Dimensions is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=8gh&AN=173970398
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        Value: 10.1016/j.gloenvcha.2023.102765
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        Text: English
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      – SubjectFull: Solar radiation management
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      – SubjectFull: Public opinion
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      – SubjectFull: Social media
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