e.g. mhealth
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Skip search results from other journals and go to results- 221 Journal of Medical Internet Research
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To achieve this, we collected and analyzed a large pool of images posted by individuals on the popular social media platform, Twitter. Twitter is one of the most diverse social media platforms in terms of user age [8]. Given that Twitter has limited contextual information due to tweet length restrictions and the increasing number of multimedia postings [9], our study uses text with image data to learn peoples’ dietary behaviors to learn about population-level dietary behavior in a more comprehensive way.
J Med Internet Res 2025;27:e51638
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Our research approach consisted of seven steps: (1) developing Twitter search terms, (2) establishing a period from which tweets would be collected, (3) using the Twitter application programming interface (API) to collect tweets within the defined search period, (4) processing tweets to enhance the accuracy of data analyses, (5) performing sentiment analysis using a Robustly Optimized BERT Pretraining Approach (Ro BERTa), (6) identifying themes among tweets through word frequency, and (7) collecting and further
J Med Internet Res 2025;27:e65087
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The Twitter application programming interface (API) for academics was used to collect tweets from January to December 2021. To analyze linguistic differences in pain-related discussions, we selected tweets from the 2 states with the highest opioid mortality rates (Florida and Ohio) and the 2 with the lowest rates (South and North Dakota) in 2021 [24].
J Med Internet Res 2025;27:e67506
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Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan
Stigma can manifest as various messages, eliciting message responses, and ultimately causing message effects, as defined by Smith’s stigma-communication model, which can be used to analyze tweets from X (formerly known as Twitter) [17]. A message refers to the intent of a tweet, such as a label intended to reinforce societal prejudices. A message response is a reaction or interaction generated by another user in relation to the initial message, such as accessing relevant social attitudes or stereotypes.
J Med Internet Res 2025;27:e69696
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One study found that about a quarter of HPV-related content on Twitter contained misinformation about the HPV vaccine. HPV vaccine misinformation posts had a higher average “like” count than pro-vaccine posts, making them more likely to be seen by broader audiences [22]. Viewing pro-HPV vaccine content on social media ironically exposes parents to antivaccine rhetoric, as pro-HPV vaccine content attracts antivaccine responses [23].
J Med Internet Res 2025;27:e54657
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Food Access in New York City During the COVID-19 Pandemic: Social Media Monitoring Study
According to a survey of Twitter users conducted by Pew Research Center in 2018, individuals of all races and genders use the platform; however, users tend to be “younger, more educated and more likely to be Democrats than general public” [11]. Furthermore, Pew noted that 80% of all tweets originate from only 10% of all users, as the median Twitter user posts only about twice per month [11].
JMIR Form Res 2025;9:e49520
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NGOs have played a significant role in catalyzing hashtag feminist movements on GBV worldwide and in Mexico by engaging stakeholders and the general public through dialogue and community-building practices, mainly through Facebook and X (formerly known as Twitter; X Corp) [21-29].
JMIR Infodemiology 2025;5:e67368
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Infoveillance of COVID-19 Infections in Dentistry Using Platform X: Descriptive Study
Among the different social media platforms, X (previously known as Twitter) is one of the most popular forms used for health care communication [11].
In the field of medicine, platform X (formerly known as Twitter) has been used as a source of social media data within the context of health care–related information [11]. X allows millions of users to send and receive “tweets” or short messages for free.
J Med Internet Res 2025;27:e54650
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Twitter (now X), a hub for real-time public discourse, has become a fertile ground for divergent views on COVID-19 treatment [4,5]. This sentiment analysis focuses on Twitter discussions about ivermectin, showing public opinion that, while not devoid of misinformation risks, these discussions offer an alternative lens to understand the societal pulse on this contentious topic [6].
JMIR Form Res 2025;9:e50536
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Impact of Social Media Influencers on Amplifying Positive Public Health Messages
twitter
J Med Internet Res 2025;27:e73062
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