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使用谷歌相关性工具量化不同人口统计群体的搜索行为。

Quantifying the Search Behaviour of Different Demographics Using Google Correlate.

作者信息

Letchford Adrian, Preis Tobias, Moat Helen Susannah

机构信息

Data Science Lab, Behavioural Science, Warwick Business School, University of Warwick, CV4 7AL, Coventry, United Kingdom.

出版信息

PLoS One. 2016 Feb 24;11(2):e0149025. doi: 10.1371/journal.pone.0149025. eCollection 2016.

DOI:10.1371/journal.pone.0149025
PMID:26910464
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4766235/
Abstract

Vast records of our everyday interests and concerns are being generated by our frequent interactions with the Internet. Here, we investigate how the searches of Google users vary across U.S. states with different birth rates and infant mortality rates. We find that users in states with higher birth rates search for more information about pregnancy, while those in states with lower birth rates search for more information about cats. Similarly, we find that users in states with higher infant mortality rates search for more information about credit, loans and diseases. Our results provide evidence that Internet search data could offer new insight into the concerns of different demographics.

摘要

我们与互联网的频繁互动正在产生关于我们日常兴趣和关注点的大量记录。在此,我们研究谷歌用户的搜索如何因美国不同州的出生率和婴儿死亡率而有所不同。我们发现,出生率较高的州的用户搜索更多关于怀孕的信息,而出生率较低的州的用户搜索更多关于猫的信息。同样,我们发现婴儿死亡率较高的州的用户搜索更多关于信贷、贷款和疾病的信息。我们的结果提供了证据,表明互联网搜索数据可以为不同人口群体的关注点提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db02/4766235/71efc4971f67/pone.0149025.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db02/4766235/ecd7e3d22ebb/pone.0149025.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db02/4766235/71efc4971f67/pone.0149025.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db02/4766235/ecd7e3d22ebb/pone.0149025.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db02/4766235/71efc4971f67/pone.0149025.g002.jpg

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Modelling human mobility patterns using photographic data shared online.利用在线共享的摄影数据建立人类移动模式模型。
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Adaptive nowcasting of influenza outbreaks using Google searches.利用谷歌搜索进行流感疫情的适应性实时预测。
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