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Twitter Discussions on #digitaldementia: Content and Sentiment Analysis.
Cho, Hyeongchan; Kim, Kyu-Min; Kim, Jee-Young; Youn, Bo-Young.
Afiliación
  • Cho H; Department of Business Administration, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
  • Kim KM; Department of Health Administration, Gyeonggi University of Science and Technology, Gyeonggi-do, Republic of Korea.
  • Kim JY; Medical R&D Center, Bodyfriend Co Ltd, Seoul, Republic of Korea.
  • Youn BY; Department of Bio-Healthcare, Hwasung Medi-Science University, Gyeonggi-do, Republic of Korea.
J Med Internet Res ; 26: e59546, 2024 Jul 16.
Article en En | MEDLINE | ID: mdl-39012679
ABSTRACT

BACKGROUND:

Digital dementia is a term that describes a possible decline in cognitive abilities, especially memory, attributed to the excessive use of digital technology such as smartphones, computers, and tablets. This concept has gained popularity in public discourse and media lately. With the increasing use of social media platforms such as Twitter (subsequently rebranded as X), discussions about digital dementia have become more widespread, which offer a rich source of information to understand public perceptions, concerns, and sentiments regarding this phenomenon.

OBJECTIVE:

The aim of this research was to delve into a comprehensive content and sentiment analysis of Twitter discussions regarding digital dementia using the hashtag #digitaldementia.

METHODS:

Retrospectively, publicly available English-language tweets with hashtag combinations related to the topic of digital dementia were extracted from Twitter. The tweets were collected over a period of 15 years, from January 1, 2008, to December 31, 2022. Content analysis was used to identify major themes within the tweets, and sentiment analysis was conducted to understand the positive and negative emotions associated with these themes in order to gain a better understanding of the issues surrounding digital dementia. A one-way ANOVA was performed to gather detailed statistical insights regarding the selected tweets from influencers within each theme.

RESULTS:

This study was conducted on 26,290 tweets over 15 years by 5123 Twitter users, mostly female users in the United States. The influencers had followers ranging from 20,000 to 1,195,000 and an average of 214,878 subscribers. The study identified four themes regarding digital dementia after analyzing tweet content (1) cognitive decline, (2) digital dependency, (3) technology overload, and (4) coping strategies. Categorized according to Glaser and Strauss's classifications, most tweets (14,492/26,290, 55.12%) fell under the categories of wretched (purely negative) or bad (mostly negative). However, only a small proportion of tweets (3122/26,290, 11.86%) were classified as great (purely positive) or swell sentiment (mostly positive). The ANOVA results showed significant differences in mean sentiment scores among the themes (F3,3581=29.03; P<.001). The mean sentiment score was -0.1072 (SD 0.4276).

CONCLUSIONS:

Various negative tweets have raised concerns about the link between excessive use of digital devices and cognitive decline, often known as digital dementia. Of particular concern is the rapid increase in digital device use. However, some positive tweets have suggested coping strategies. Engaging in digital detox activities, such as increasing physical exercise and participating in yoga and meditation, could potentially help prevent cognitive decline.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Demencia / Medios de Comunicación Sociales Límite: Humans Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Demencia / Medios de Comunicación Sociales Límite: Humans Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article