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The devil we know and the angel that did not fly: An examination of devil/angel shift in twitter fracking “debates” in NY 2008–2018

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  • Andrew Pattison
  • William Cipolli
  • Jose Marichal

Abstract

Recent work has applied the Narrative Policy Framework (NPF) to examine narrative strategies in policy debates on social media platforms. We contribute to the literature by applying the NPF to fracking policy debates in New York using well‐established Natural Language Processing tools, including sentiment analysis. We combine this computational approach with a qualitative hand‐coding of pro‐ and antifracking Twitter influentials. This approach allows us to consider a much larger corpus of tweets over a much longer time frame than has been done thus far. We adapt and test NPF propositions related to the use of the devil/angel shift strategies before and after a major state‐wide policy change, that is, a state‐wide moratorium on high volume hydraulic fracturing or fracking. Overall, we find evidence for the use of the devil shift narrative strategy by the pro‐fracking coalition aimed at the Governor prior to the moratorium. After the moratorium, the relative percentage of Tweets containing devil shift sentiments decreases as the pro‐fracking coalition generally downshifts in its use of angel shift language without a corresponding increase in devil shift language, whereas, conversely, the anti‐fracking coalition generally downshifts in its use of devil shift language without a general increase in angel shift language. When we shifted our analysis to Tweets containing fracking and the Governor, we found a similar postban decrease in devil shift language among anti‐fracking users. Our findings offer lessons for using computational tools in the NPF as an approach to expand analytic ability and for the operationalization of concepts such as narrative strategies and policy entrepreneurs. 近年来, 研究聚焦于应用叙事政策框架 (NPF) 分析社交媒体平台上政策辩论所使用的叙事策略。通过使用包括情感分析在内的自然语言处理 (NLP) 工具, 我们对纽约州水力压裂政策辩论应用NPF, 进而对相关文献作贡献。我们对支持和反对水力压裂的推特名人 (的推文) 进行定性手动编码, 并与该计算方法相结合。与以往相比, 此法允许我们衡量更长时间段内的更多推文语料库。我们对一系列NPF观点加以适应和检验, 这些观点有关于重要州级政策变革 (即暂停高容量水力压裂) 前后的丑化政治对手/美化政治盟友 (devil/angel shift) 策略的使用。整体而言, 我们发现, 支持水力压裂的联盟在计划暂停之前对州长采取了丑化政治对手的叙事策略。暂停计划实施后, 含有丑化政治对手情感的推文的相对占比有所减少, 因为支持水力压裂的联盟基本降低使用了美化政治盟友的语言, 同时没有增加其丑化政治对手的语言, 相反的是, 反水力压裂的联盟基本降低使用了丑化政治对手的语言, 同时没有增加其美化政治盟友的语言。当我们将分析聚焦于包含水力压裂和州长的推文时, 发现反水力压裂的用户也类似地在暂停计划实施后减少了丑化政治对手的语言。我们的研究发现为以下两点提供了经验: (1)在NPF中使用计算工具以扩大分析能力; (2)对例如叙事策略及政策企业家等概念进行操作化。 El trabajo reciente ha aplicado el Marco de Política Narrativa (NPF) para examinar las estrategias narrativas en los debates de políticas en las plataformas de redes sociales. Contribuimos a la literatura aplicando el NPF a los debates sobre políticas de fracking en Nueva York utilizando herramientas de procesamiento del lenguaje natural (NLP) bien establecidas, incluido el análisis de sentimientos. Combinamos este enfoque computacional con una codificación manual cualitativa de los influyentes de Twitter a favor y en contra del fracking. Este enfoque nos permite considerar un corpus de tweets mucho más grande durante un período de tiempo mucho más largo de lo que se ha hecho hasta ahora. Adaptamos y probamos las propuestas de NPF relacionadas con el uso de las estrategias de cambio diablo / ángel antes y después de un cambio importante de política en todo el estado, es decir, una moratoria en todo el estado sobre la fracturación hidráulica de alto volumen o el fracking. En general, encontramos evidencia del uso de la estrategia narrativa del cambio diabólico por parte de la coalición pro‐fracking dirigida al gobernador antes de la moratoria. Después de la moratoria, el porcentaje relativo de Tweets que contienen sentimientos de cambio diabólico disminuye a medida que la coalición pro‐fracking generalmente reduce su uso del lenguaje de cambio de ángeles sin un aumento correspondiente en el lenguaje de cambio diabólico, mientras que, por el contrario, la coalición anti‐fracking generalmente cambia de turno. en su uso del lenguaje de cambio de diablo sin un aumento general en el lenguaje de cambio de ángel. Cuando cambiamos nuestro análisis a los Tweets que contenían fracking y el gobernador, encontramos una disminución similar posterior a la prohibición en el lenguaje del diablo entre los usuarios anti‐fracking. Nuestros hallazgos ofrecen lecciones para el uso de herramientas computacionales en el NPF como un enfoque para expandir la capacidad analítica y para la operacionalización de conceptos tales como estrategias narrativas y emprendedores de políticas.

Suggested Citation

  • Andrew Pattison & William Cipolli & Jose Marichal, 2022. "The devil we know and the angel that did not fly: An examination of devil/angel shift in twitter fracking “debates” in NY 2008–2018," Review of Policy Research, Policy Studies Organization, vol. 39(1), pages 51-72, January.
  • Handle: RePEc:bla:revpol:v:39:y:2022:i:1:p:51-72
    DOI: 10.1111/ropr.12452
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    References listed on IDEAS

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    1. Colette S. Vogeler & Nils C. Bandelow, 2018. "Mutual and Self Perceptions of Opposing Advocacy Coalitions: Devil Shift and Angel Shift in a German Policy Subsystem," Review of Policy Research, Policy Studies Organization, vol. 35(5), pages 717-732, September.
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    4. Andrew Pattison, 2018. "Factors Shaping Policy Learning: A Study of Policy Actors in Subnational Climate and Energy Issues," Review of Policy Research, Policy Studies Organization, vol. 35(4), pages 535-563, July.
    5. Hannes R. Stephan, 2020. "Shaping the Scope of Conflict in Scotland’s Fracking Debate: Conflict Management and the Narrative Policy Framework," Review of Policy Research, Policy Studies Organization, vol. 37(1), pages 64-91, January.
    6. Christopher M. Weible & Tanya Heikkila, 2016. "Comparing the Politics of Hydraulic Fracturing in New York, Colorado, and Texas," Review of Policy Research, Policy Studies Organization, vol. 33(3), pages 232-250, May.
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