使用ChatGPT从YouTube字幕中进行意见挖掘：以2023年土耳其大选街头采访民意调查为例
Opinion Mining from YouTube Captions Using ChatGPT: A Case Study of Street Interviews Polling the 2023 Turkish Elections
AI总结：
本文提出使用ChatGPT从YouTube自动生成的街头采访字幕中挖掘意见，以2023年土耳其大选为例，ChatGPT预测首选候选人准确率达97%，识别投票动机准确率达71%，为社交媒体意见挖掘提供了低噪高效的新方法。
摘要：
意见挖掘在理解公众情绪和偏好方面发挥着关键作用，特别是在政治选举的背景下。传统的民意调查方法虽然有用，但可能成本高昂且可扩展性较差。社交媒体为意见挖掘提供了另一种数据来源，但在数据收集方面存在噪声、偏差和平台限制等挑战。在本文中，我们提出了一种新的意见挖掘方法，利用YouTube自动生成的字幕作为数据源，特别以2023年土耳其大选作为案例研究。我们引入了一个使用ChatGPT的意见挖掘框架，用于大规模标注投票意向和动机，这些意向和动机代表了选举前的立场和框架。我们报告称，ChatGPT能以97%的准确率预测首选候选人，并根据从325次访谈中收集的数据，以71%的准确率从13个可能选项中识别出正确的投票动机。最后，我们讨论了该方法的稳健性，考虑了字幕质量、访谈长度和频道等因素。这种新方法将为使用社交媒体数据进行意见挖掘提供一种噪声更小、更具成本效益的替代方案。
英文摘要：
Opinion mining plays a critical role in understanding public sentiment and preferences, particularly in the context of political elections. Traditional polling methods, while useful, can be expensive and less scalable. Social media offers an alternative source of data for opinion mining but presents challenges such as noise, biases, and platform limitations in data collection. In this paper, we propose a novel approach for opinion mining, utilizing YouTube's auto-generated captions from public interviews as a data source, specifically focusing on the 2023 Turkish elections as a case study. We introduce an opinion mining framework using ChatGPT to mass-annotate voting intentions and motivations that represent the stance and frames prior to the election. We report that ChatGPT can predict the preferred candidate with 97\% accuracy and identify the correct voting motivation out of 13 possible choices with 71\% accuracy based on the data collected from 325 interviews. We conclude by discussing the robustness of our approach, accounting for factors such as captions quality, interview length, and channels. This new method will offer a less noisy and cost-effective alternative for opinion mining using social media data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
