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Skip search results from other journals and go to results- 219 Journal of Medical Internet Research
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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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At the time of data extraction, direct Twitter (subsequently rebranded as X) engagement with the paper yielded 165,720 tweets from 81,861 users with an upper bound of 11,094,945 followers, 181 media mentions, and a total altmetric score of 45,844. This investigative piece suggested that Pfizer vaccine trials were compromised by the unblinding of subjects and data falsification.
J Med Internet Res 2025;27:e64679
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Profiling Generalized Anxiety Disorder on Social Networks: Content and Behavior Analysis
Vedula and Parthasarathy [19] studied the behaviors of people with depression on Twitter, whereas Peng et al [42] analyzed the depressive characteristics of Sina Weibo users based on posts and user profiles.
J Med Internet Res 2025;27:e53399
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