Assessment of the relationship between Google Trends search data and national suicide rates in Turkey

O. Ekinci, Fadime ay, Al Koyuncu, Feyza Soy, Or etin, Feyza ce
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Abstract

Objective: The present study aimed to examine possible relationships between suicide-related terms obtained from Google Trends and actual suicide data and whether these relationships differ according to sex. Materials and Methods: The study period was from 2009 to 2019. In this study, suicide data were collected from the suicide statistics of the Turkish Statistical Institute (TUIK) for this timeframe. Google Trends was used to examine the search trends of suicide-related terms in Turkey. Pearson correlation analysis was used to find associations between the data obtained from TUIK and Google Trends. Finally, linear regression analysis was performed to identify predictors of monthly completed suicide rates in the general population. Results: In our study, 105 search terms obtained from Google Trends were examined to find associations with suicide rates in a specific timeframe. Among them, 31 terms had positive correlations, and nine had significant negative correlations. The terms "allergy" and "pain" were the most closely related to the overall suicide rates. Other significantly correlated terms were "how to commit suicide," "to commit suicide," "depression," and "hallucination." In addition, significantly different results were found for men and women. Conclusion: The present study showed that suicide-related terms obtained from Google Trends may predict actual suicide rates and may be an easy way to monitor suicide trends in Turkey. Future studies should use a more comprehensive internet network, including social media and other search engines, and consider other variables related to suicide to better understand this relationship.
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评估谷歌趋势搜索数据与土耳其全国自杀率之间的关系
目的:本研究旨在检验从谷歌趋势中获得的自杀相关术语与实际自杀数据之间可能存在的关系,以及这些关系是否因性别而异。材料与方法:研究时间为2009 - 2019年。在本研究中,自杀数据收集自土耳其统计研究所(TUIK)的自杀统计数据。谷歌趋势被用来检查土耳其自杀相关术语的搜索趋势。使用Pearson相关分析来发现从TUIK获得的数据与Google Trends之间的关联。最后,进行线性回归分析以确定一般人群每月完成自杀率的预测因子。结果:在我们的研究中,我们检查了从谷歌趋势中获得的105个搜索词,以找出特定时间段内自杀率的关联。其中31项呈正相关,9项呈显著负相关。“过敏”和“疼痛”这两个词与总体自杀率关系最为密切。其他显著相关的词汇还有“如何自杀”、“自杀”、“抑郁”和“幻觉”。此外,男性和女性的结果也有显著差异。结论:目前的研究表明,从谷歌趋势中获得的与自杀相关的术语可以预测实际的自杀率,并且可能是监测土耳其自杀趋势的一种简单方法。未来的研究应该使用更全面的互联网网络,包括社交媒体和其他搜索引擎,并考虑与自杀相关的其他变量,以更好地理解这种关系。
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