Social media split testing and message framing: Emerging capacities to encourage residential water conservation

C. Silvert, L. Warner, J. Loizzo, Jarred Shellhouse
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引用次数: 1

Abstract

Abstract Water conservation in residential landscapes remains essential to mitigate projected global water shortages. Social media has seldom been used to drive engagement in conservation and may be an important channel for environmental change agents to communicate to clientele and promote behavior changes. We tested messages framed with real conservation facts and narrative quotes using the split testing technique. Data were collected in real-time on Facebook and Instagram on users’ engagement with water conservation messages/ads and visits to a website to learn more. We found users are more likely to engage with relatable messages containing impressive numbers and perceived measurable benefits.
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社会媒体分离测试和信息框架:鼓励住宅节水的新兴能力
住宅景观中的节水对于缓解预计的全球水资源短缺至关重要。社会媒体很少被用来推动保护的参与,它可能是环境变化代理人与客户沟通并促进行为改变的重要渠道。我们使用分裂测试技术测试带有真实保护事实和叙述性引用的信息。在Facebook和Instagram上实时收集用户参与节水信息/广告以及访问网站以了解更多信息的数据。我们发现,用户更有可能与包含令人印象深刻的数字和可衡量的利益的相关信息互动。
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
15
期刊介绍: Applied Artificial Intelligence addresses concerns in applied research and applications of artificial intelligence (AI). The journal also acts as a medium for exchanging ideas and thoughts about impacts of AI research. Articles highlight advances in uses of AI systems for solving tasks in management, industry, engineering, administration, and education; evaluations of existing AI systems and tools, emphasizing comparative studies and user experiences; and the economic, social, and cultural impacts of AI. Papers on key applications, highlighting methods, time schedules, person-months needed, and other relevant material are welcome.
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