J 2024

Uncovering the Top Nonadvertising Weight Loss Websites on Google : A Data-Mining Approach

ALMENARA, Carlos Arturo and Hayriye GÜLEC

Basic information

Original name

Uncovering the Top Nonadvertising Weight Loss Websites on Google : A Data-Mining Approach

Authors

ALMENARA, Carlos Arturo and Hayriye GÜLEC

Edition

JMIR Infodemiology, Toronto, JMIR Publications, 2024, 2564-1891

Other information

Language

English

Type of outcome

Article in a journal

Country of publisher

Canada

Confidentiality degree

is not subject to a state or trade secret

References:

Organization

Fakulta sociálních studií – Repository – Repository

UT WoS

001378882800001

EID Scopus

2-s2.0-85214533813

Keywords in English

consumer health informatics; cyberattack risk; data mining; Google; information seeking; weight loss; online health information; website analysis; digital health; internet search

Links

LX22NPO5101, research and development project.
Changed: 30/1/2025 00:51, RNDr. Daniel Jakubík

Abstract

V originále

Background: Online weight loss information is commonly sought by internet users, and it may impact their health decisions and behaviors. Previous studies examined a limited number of Google search queries and relied on manual approaches to retrieve online weight loss websites. Objective: This study aimed to identify and describe the characteristics of the top weight loss websites on Google. Methods: This study gathered 432 Google search queries collected from Google autocomplete suggestions, "PeopleAlso Ask" featured questions, and GoogleTrends data. A data-mining softwaretool was developed to retrievethe search results automatically, setting English and the United States as the default criteria for language and location, respectively. Domain classification and evaluation technologies were used to categorize the websites according to their content and determine their risk of cyberattack. In addition, the top 5 most frequent websites in nonadvertising (ie, nonsponsored) search results were inspected for quality. Results: The results revealed that the top 5 nonadvertising websites were healthline.com, webmd.com, verywellfit.com, mayoclinic.org, and womenshealthmag.com. All provided accuracy statements and author credentials. The domain categorization taxonomy yielded a total of 101 unique categories. After grouping the websites that appeared less than 5 times, the most frequent categories involved "Health" (104/623, 16.69%), "Personal Pages and Blogs" (91/623, 14.61%), "Nutrition and Diet" (48/623, 7.7%), and "Exercise" (34/623, 5.46%). The risk of being a victim of a cyberattack was low. Conclusions:The findings suggested that while quality information is accessible, users may still encounter less reliable content among various online resources. Therefore, better tools and methods are needed to guide users toward trustworthy weight loss information.

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