Purpose

The purpose of this paper is to examine how upstream social marketing can benefit from using social media commentary to identify cognitive biases. Using reactions to leading media/news publications/articles related to climate and energy policy in Australia, this paper aims to understand underlying community cognitive biases and their reasonings.

Design/methodology/approach

Social listening was used to gather community commentary about climate and energy policy in Australia. This allowed the coding of natural language data to determine underlying cognitive biases inherent in the community. In all, 2,700 Facebook comments were collected from 27 news articles dated between January 2018 and March 2020 using exportcomments.com. Team coding was used to ensure consistency in interpretation.

Findings

Nine key cognitive bias were noted, including, pessimism, just-world, confirmation, optimum, curse of knowledge, Dunning–Kruger, self-serving, concision and converge biases. Additionally, the authors report on the interactive nature of these biases. Right-leaning audiences are perceived to be willfully uninformed and motivated by self-interest; centric audiences want solutions based on common-sense for the common good; and left-leaning supporters of progressive climate change policy are typically pessimistic about the future of climate and energy policy in Australia. Impacts of powerful media organization shaping biases are also explored.

Research limitations/implications

Through a greater understanding of the types of cognitive biases, policy-makers are able to better design and execute influential upstream social marketing campaigns.

Originality/value

The study demonstrates that observing cognitive biases through social listening can assist upstream social marketing understand community biases and underlying reasonings towards climate and energy policy.

中文翻译：

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利用社交聆听探索消费者认知偏差：对上游社交营销的影响

目的

本文的目的是研究上游社交营销如何从使用社交媒体评论来识别认知偏差中受益。本文利用对澳大利亚气候和能源政策相关主要媒体/新闻出版物/文章的反应，旨在了解潜在的社区认知偏见及其推理。

设计/方法/方法

社会倾听被用来收集关于澳大利亚气候和能源政策的社区评论。这使得自然语言数据的编码能够确定社区固有的潜在认知偏差。总共使用 exportcomments.com 从 2018 年 1 月至 2020 年 3 月之间的 27 篇新闻文章中收集了 2,700 条 Facebook 评论。团队编码用于确保解释的一致性。

发现

注意到九个关键的认知偏差，包括悲观主义、公正世界、确认、最优、知识诅咒、邓宁-克鲁格、自私、简洁和趋同偏差。此外，作者还报告了这些偏见的交互性。右倾观众被认为是故意不知情并受自身利益驱使；为了共同利益，中心受众需要基于常识的解决方案；进步气候变化政策的左倾支持者通常对澳大利亚气候和能源政策的未来持悲观态度。还探讨了强大的媒体组织塑造偏见的影响。

研究限制/影响

通过更深入地了解认知偏差的类型，政策制定者能够更好地设计和执行有影响力的上游社会营销活动。

原创性/价值

该研究表明，通过社会倾听观察认知偏差可以帮助上游社会营销了解社区偏见以及对气候和能源政策的潜在推理。