Google Trends (GT) data are increasingly used in the social sciences and adjacent fields. However, previous research on the quality of GT data has raised concerns regarding their reliability. In the present study, we investigated whether reliability differs between low- and high-frequency search terms. In other words, we explored the existence of a reliability-frequency continuum in GT data. Our study adds to previous research by investigating a more comprehensive set of search terms and different aspects of reliability (e.g., differences in relative search volume distributions, correctly identified maxima). For this purpose, we collected samples of GT data for ten high- and two low-frequency search terms. We obtained one real-time sample and 62 non–realtime samples per search term (30 non–realtime samples for low-frequency search terms). Data collection was restricted to search data for Germany. Our data support the existence of a reliability-frequency continuum—low-frequency search terms are subject to greater reliability issues compared to high-frequency search terms. Based on our findings, we have derived practical recommendations for the use of GT data and have outlined future research opportunities.

中文翻译：

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使用 Google 趋势数据研究高频搜索词：可靠性-频率连续体的证据


Google Trends （GT） 数据越来越多地用于社会科学和相邻领域。然而，之前对 GT 数据质量的研究引起了对其可靠性的担忧。在本研究中，我们调查了低频和高频搜索词之间的可靠性是否不同。换句话说，我们探索了 GT 数据中可靠性-频率连续体的存在。我们的研究通过调查更全面的搜索词集和可靠性的不同方面（例如，相对搜索量分布的差异、正确识别的最大值）来补充以前的研究。为此，我们收集了 10 个高频和 2 个低频搜索词的 GT 数据样本。我们为每个搜索词获得了 1 个实时样本和 62 个非实时样本（低频搜索词为 30 个非实时样本）。数据收集仅限于搜索德国的数据。我们的数据支持可靠性-频率连续体的存在——与高频搜索词相比，低频搜索词容易受到更大的可靠性问题的影响。根据我们的研究结果，我们得出了使用 GT 数据的实用建议，并概述了未来的研究机会。