Přehled o publikaci
2024
Uncovering the Top Nonadvertising Weight Loss Websites on Google : A Data-Mining Approach
ALMENARA, Carlos Arturo and Hayriye GÜLECBasic 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.