2022
DOI: 10.1016/j.enpol.2022.113070
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Short and long-term dominance of negative information in shaping public energy perceptions: The case of shallow geothermal systems

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Cited by 12 publications
(4 citation statements)
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“…Increasing subjective knowledge about the sector was revealed as potentially acceptance-hindering, given the importance of emotions for beliefs and behaviors (Spampatti et al 2022), although its significant influence was limited to negative components and did not notably correlate with lower acceptability. Subjective knowledge as a critical lens on system changes was found by Linzenich et al (2020) regarding large-scale energy infrastructure technologies.…”
Section: Discussionmentioning
confidence: 91%
“…Increasing subjective knowledge about the sector was revealed as potentially acceptance-hindering, given the importance of emotions for beliefs and behaviors (Spampatti et al 2022), although its significant influence was limited to negative components and did not notably correlate with lower acceptability. Subjective knowledge as a critical lens on system changes was found by Linzenich et al (2020) regarding large-scale energy infrastructure technologies.…”
Section: Discussionmentioning
confidence: 91%
“…Platforms have provided similar contextual information about companies in other settings—for example, Google Flights displays carbon emissions data alongside flight prices when people select a flight to purchase among several options 52 . Enabling consumers to view such information at the point of purchase could provide a stronger incentive for companies to steer their advertisements away from such outlets, especially since the effect of negative information can persist for several months 53 . Overall, these interventions could decrease the inadvertent advertising revenue going towards misinformation outlets, which could eventually lead to such sites ceasing to operate, as observed anecdotally in prior work 29 .…”
Section: Discussionmentioning
confidence: 99%
“…From a final pool of N = 1,033 tweets identified as climate related and disinformation/delay, we identified N = 79 tweets that were understandable without requiring background information and not including country-specific aspects. These 79 tweets were pretested with a representative sample of N = 504 British participants on the data collection platform Prolific ( https://www.prolific.co/ ), in terms of their impact on affect towards climate action and 12 further variables—for example, perceived political slant—that may affect processing of disinformation about political topics 203 (the full list of disinformation, with a description of the pretesting design and all validation materials and data, can be found at https://osf.io/m58zx ). Among these 79 statements, we selected N = 20 disinformation statements (Table 3 ) that deviated the least from the mean ratings across all 15 validation measures, evenly divided between 10 disinformation statements about climate science and 10 disinformation statements to delay climate action (according to coding criteria developed in previous research 14 , 33 ).…”
Section: Methodsmentioning
confidence: 99%