烟草控制的人工智能:使用大型语言模型识别促进烟草的社交媒体内容
Hüseyin Küçükali1,2, Mehmet Sarper Erdoğan3
1Centre for Public Health, Queen's University Belfast, Belfast, UK.
概括
开发了一种人工智能工具,可以在社交媒体上自动检测烟草宣传,帮助烟草控制工作. 这种人工智能模型精确地识别营销策略,使更好的监控和政策执行成为可能.
科学领域:
- 人工智能的人工智能
- 公共卫生 公共卫生
- 数字营销 数字营销 数字营销
背景情况:
- 烟草公司利用社交媒体来规避营销限制.
- 在社交媒体上监控烟草推广是具有挑战性的,但对公共卫生至关重要.
- 暴露在社交媒体上的烟草营销与增加的吸烟行为有关.
研究的目的:
- 开发一种人工智能 (AI) 工具,用于在社交媒体上自动识别烟草宣传内容.
- 分析在社交媒体平台上使用的烟草推广机制.
- 通过改进内容监督,加强烟草控制战略.
主要方法:
- 采用混合方法的方法,分析了土耳其语的177,684条与烟草有关的推文.
- 诱导性内容分析确定了主要的烟草推广机制.
- 基于变压器的大型语言模型 (LLM) 在标记的数据集上进行了微调,以实现精确的预测.
主要成果:
- 关键的推广机制包括行为建模,积极态度表达,使用建议和品牌营销.
- 开发的AI模型在识别烟草宣传方面实现了87.8%的回忆率和81.1%的精度.
- 该模型的实用性通过对推特上的烟草推广进行为期一个月的分析来验证.
结论:
- 人工智能工具可以有效监控烟草推广的社交媒体,支持烟草控制政策和实践.
- 这项技术为监控,执法和健康促进倡议提供了新的机会.
- 基于LLM的方法与现有的烟草控制方法相比,提供了更高的预测性能.
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