Přehled o publikaci
2024
Uncovering the Top Nonadvertising Weight Loss Websites on Google : A Data-Mining Approach
ALMENARA, Carlos Arturo a Hayriye GÜLECZákladní údaje
Originální název
Uncovering the Top Nonadvertising Weight Loss Websites on Google : A Data-Mining Approach
Autoři
ALMENARA, Carlos Arturo a Hayriye GÜLEC
Vydání
JMIR Infodemiology, Toronto, JMIR Publications, 2024, 2564-1891
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Stát vydavatele
Kanada
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Organizace
Fakulta sociálních studií – Masarykova univerzita – Repozitář
UT WoS
001378882800001
EID Scopus
2-s2.0-85214533813
Klíčová slova anglicky
consumer health informatics; cyberattack risk; data mining; Google; information seeking; weight loss; online health information; website analysis; digital health; internet search
Návaznosti
LX22NPO5101, projekt VaV.
Změněno: 30. 1. 2025 00:51, RNDr. Daniel Jakubík
Anotace
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.