Using Google Trends Data to Study High-Frequency Search Terms: Evidence for a Reliability-Frequency Continuum

IF 3 2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Social Science Computer Review Pub Date : 2024-10-12 DOI:10.1177/08944393241279421

Tobias Gummer, Anne-Sophie Oehrlein

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Abstract

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.

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利用谷歌趋势数据研究高频搜索词：可靠性-频率连续性的证据

谷歌趋势（GT）数据越来越多地应用于社会科学及邻近领域。然而，以往对 GT 数据质量的研究引起了人们对其可靠性的担忧。在本研究中，我们调查了低频搜索词和高频搜索词之间的可靠性是否存在差异。换句话说，我们探讨了 GT 数据中是否存在可靠性-频率连续体。我们的研究对以往的研究进行了补充，调查了更全面的搜索词集合和可靠性的不同方面（如相对搜索量分布的差异、正确识别的最大值）。为此，我们收集了十个高频搜索词和两个低频搜索词的 GT 数据样本。我们获得了每个搜索词的一个实时样本和 62 个非实时样本（低频搜索词有 30 个非实时样本）。数据收集仅限于德国的搜索数据。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，低频搜索词的可靠性问题更大。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。

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来源期刊

Social Science Computer Review 社会科学-计算机：跨学科应用

CiteScore

9.00

自引率

4.90%

发文量

审稿时长

>12 weeks

期刊介绍： Unique Scope Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of informational technology. Topics included: artificial intelligence, business, computational social science theory, computer-assisted survey research, computer-based qualitative analysis, computer simulation, economic modeling, electronic modeling, electronic publishing, geographic information systems, instrumentation and research tools, public administration, social impacts of computing and telecommunications, software evaluation, world-wide web resources for social scientists. Interdisciplinary Nature Because the Uses and impacts of computing are interdisciplinary, so is Social Science Computer Review. The journal is of direct relevance to scholars and scientists in a wide variety of disciplines. In its pages you''ll find work in the following areas: sociology, anthropology, political science, economics, psychology, computer literacy, computer applications, and methodology.