The use and impact of Twitter at medical conferences: Best practices and Twitter etiquette

The use of social media, and in particular, Twitter, for professional use among healthcare providers is rapidly increasing across the world. One medical subspecialty that is leading the integration of this new platform for communication into daily practice and for information dissemination to the general public is the field of hematology/oncology. A growing amount of research in this area demonstrates that there is increasing interest among physicians to learn not only how to use social media for consumption of educational material, but also how to generate and contribute original content in one’s interest/expert areas. One aspect in which this phenomenon has been highlighted is at the time of maximum new information presentation: at a major medical conference. Hematologists/oncologists are engaging regularly in one of the most common forms of social media, Twitter, during major medical conferences, for purposes of debate, discussion, and real-time evaluation of the data being presented. As interest has grown in this area, this article aims to review the new norms, practices, and impact of using Twitter at the time of medical conferences, and also explores some of the barriers and pitfalls that users are encountering in this emerging field.     

Bots are less central than verified accounts during contentious political events

Information manipulation is widespread in today’s media environment. Online networks have disrupted the gatekeeping role of traditional media by allowing various actors to influence the public agenda; they have also allowed automated accounts (or bots) to blend with human activity in the flow of information. Here, we assess the impact that bots had on the dissemination of content during two contentious political events that evolved in real time on social media. We focus on events of heightened political tension because they are particularly susceptible to information campaigns designed to mislead or exacerbate conflict. We compare the visibility of bots with human accounts, verified accounts, and mainstream news outlets. Our analyses combine millions of posts from a popular microblogging platform with web-tracking data collected from two different countries and timeframes. We employ tools from network science, natural language processing, and machine learning to analyze the diffusion structure, the content of the messages diffused, and the actors behind those messages as the political events unfolded. We show that verified accounts are significantly more visible than unverified bots in the coverage of the events but also that bots attract more attention than human accounts. Our findings highlight that social media and the web are very different news ecosystems in terms of prevalent news sources and that both humans and bots contribute to generate discrepancy in news visibility with their activity.

Online networks have become an important channel for the distribution of news. Platforms like Twitter have created a public domain in which longstanding gatekeeping roles lose prominence and nontraditional media actors can also shape the agenda, increasing the public representation of voices that would otherwise be ignored (1, 2). The role of online networks is particularly crucial to launch mobilizations, gain traction in collective action efforts, and increase the visibility of political issues (3–8). However, online networks have also created an information ecosystem in which automated accounts (human and software-assisted accounts, such as bots) can hijack communication streams for opportunistic reasons [e.g., to trigger collective attention (9, 10), gain status (11, 12), and monetize public attention (13)] or with malicious intent [e.g., to diffuse disinformation (14, 15) and seed discord (16)]. During contentious political events, such as demonstrations, strikes, or acts of civil disobedience, online networks carry benefits and risks: They can be tools for organization and awareness or tools for disinformation and conflict. However, it is unclear how human, bot, and media accounts interact in the coverage of those events, or whether social media activity increases the visibility of certain sources of information that are not so prominent elsewhere online. Here, we cast light on these information dynamics, and we measure the relevance of unverified bots in the coverage of protest activity, especially as they compare to public interest accounts.Prior research has documented that a high fraction of active Twitter accounts are bots (17); that bots are responsible for much disinformation during election periods (18, 19); and that bots exacerbate political conflict by targeting social media users with inflammatory content (20). Past research has also looked at the role bots play in the diffusion of false information, showing that they amplify low-credibility content in the early stages of diffusion (21) but also that they do not discriminate between true and false information (i.e., bots accelerate the spread of both) and that, instead, human accounts are more likely to spread false news (22). Following this past work, this paper aims to determine whether bots distort the visibility of legitimate news accounts as defined by their audience reach off-platform. Unlike prior work, we connect Twitter activity with audience data collected from the web to determine whether the social media platform changes the salience that legitimate news sources have elsewhere online and, if so, determine whether bots are responsible for that distortion. We combine web-tracking data with social media data to characterize the visibility of legitimate news sources and analyze how bots create differences in the news environment. This is a particularly relevant question in the context of noninstitutional forms of political participation (like the protests we analyze here) because of their unpredictable and volatile nature.The use of the label “bot” often blurs the diversity that the category still contains. This label serves as a shorthand for accounts that can be fully or partially automated, but accounts that exhibit bot-like behavior can have very different goals and levels of human involvement in their operation. Traditional news organizations, for instance, manage many of the accounts usually classified as bots—but these accounts are actually designed to push legitimate news content. Other accounts with bot-like behavior belong to journalists and public figures—many of which are actually verified by the platform to let users know that their accounts are authentic and of public interest. Past research does not shed much light on how different types of bots enable exposure to news from legitimate sources, or how the attention they attract compares to the reach of mainstream news—which also generate a large share of social media activity (23–25). More generally, previous work does not address the question of how news visibility on social media relates to other online sources (most prominently, the web), especially in a comparative context where different political settings other than the United States are considered. Are bots effective in shifting the focus of attention as it emerges elsewhere online?This paper addresses these questions by analyzing Twitter and web-tracking data in the context of two contentious political events. The first is the Gilets Jaunes (GJ) or Yellow Vests movement, which erupted in France at the end of 2018 to demand economic justice. The second is the Catalan referendum for independence from Spain, which took place on October 1 (1-O) of 2017 as an act of civil disobedience. These two events were widely covered by mainstream media (nationally and internationally), but they also generated high volumes of social media activity, with Twitter first channeling the news that was coming out of street actions and confrontations with the police. According to journalistic accounts, Twitter helped fuel political feuds by enabling bots to exacerbate conflict (26, 27). Our analyses aim to compare the attention that unverified bot accounts received during these events of intense political mobilization with the visibility of verified and mainstream media accounts, contextualizing that activity within the larger online information environment. In particular, we want to determine whether there is a discrepancy in the reach of news sources across channels (i.e., social media and the web) and, if so, determine whether bot activity helps explain that discrepancy (e.g., for instance, by having bots retweet sources that are less visible on the web). Ultimately, our analyses aim to identify changes in the information environment to which people are exposed depending on the channel they use to access news—a process of particular relevance during fast-evolving political events of heightened social tension.     

Mining twitter to understand the smoking cessation barriers

Smoking cessation is challenging and lack of positive support is a known major barrier to quitting cigarettes.Previous studies have suggested that social influences might increase smokers' awareness of social norms for appropriate behavior,which might lead to smoking cessation.Although social media use is increasing among young adults in the United States,research on the relationship between social media use and smoking cessation is lacking.Twitter has provided a rich source of information for researchers,but no overview exists as to how the field uses Twitter in smoking cessation research.To the best of our knowledge,this study conducted a data mining analysis of Twitter to assess barriers to smoking cessation.In conclusion,Twitter is a cost-effective tool with the potential to disseminate information on the benefits of smoking cessation and updated research to the Twitter community on a global scale.     

Social Media for the Hepato-Pancreato-Biliary community (#SoMe4HPB): connecting a specialized online group for scientific and clinical knowledge dissemination

BackgroundSocial media has an increasingly important role in scientific communication, clinical discussions and knowledge distribution. While several surgical disciplines have taken to internet for increased connectivity, there is currently little knowledge about the social media activity in the field of hepatopancreatobiliary surgery. We aimed to evaluate the implementation and use of a specific HPB hashtag and Twitter handle.MethodsThe hashtag and Twitter handle (#SoMe4HPB; @hpb_so) were initiated on February 2019. We evaluated the response during the initial 15 months by applying NodeXL to trace activity.ResultsThe Twitter handle had 1388 followers (by May 7, 2020) and had generated 855 tweets and retweets. A total of 1120 mentions of 182 accounts were recorded in original tweets by @hpb_so. The largest global reach was recorded in December 2019 (254.000 people). Pancreatic cancer was the subject of 15% of all posts, liver malignancies of 12% of all posts and minimally invasive surgery of 8%.ConclusionThe Social Media for the Hepato-Pancreato-Biliary community (#SoMe4HPB) and its associated Twitter handle @hpb_so had a well-built inception followed by a progressive development connecting individuals interested in HPB Surgery internationally. The involvement of more actors is required in order to fully attain its scientific dissemination role.     

Out-group animosity drives engagement on social media

There has been growing concern about the role social media plays in political polarization. We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts and US congressional members (n = 2,730,215), we found that posts about the political out-group were shared or retweeted about twice as often as posts about the in-group. Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%. Out-group language consistently emerged as the strongest predictor of shares and retweets: the average effect size of out-group language was about 4.8 times as strong as that of negative affect language and about 6.7 times as strong as that of moral-emotional language—both established predictors of social media engagement. Language about the out-group was a very strong predictor of “angry” reactions (the most popular reactions across all datasets), and language about the in-group was a strong predictor of “love” reactions, reflecting in-group favoritism and out-group derogation. This out-group effect was not moderated by political orientation or social media platform, but stronger effects were found among political leaders than among news media accounts. In sum, out-group language is the strongest predictor of social media engagement across all relevant predictors measured, suggesting that social media may be creating perverse incentives for content expressing out-group animosity.

According to a recent article in the Wall Street Journal, a Facebook research team warned the company in 2018 that their “algorithms exploit the human brain’s attraction to divisiveness.” This research was allegedly shut down by Facebook executives, and Facebook declined to implement changes proposed by the research team to make the platform less divisive (1). This article is consistent with concerns that social media might be incentivizing the spread of polarizing content. For instance, Twitter CEO Jack Dorsey has expressed concern about the popularity of “dunking” (i.e., mocking or denigrating one’s enemies) on the platform (2). These concerns have become particularly relevant as social media rhetoric appears to have incited real-world violence, such as the recent storming of the US Capital (3). We sought to investigate whether out-group animosity was associated with increased virality on two of the largest social media platforms: Facebook and Twitter.A growing body research has examined the potential role of social media in exacerbating political polarization (4, 5). A large portion of this work has centered on the position that social media sorts us into “echo chambers” or “filter bubbles” that selectively expose people to content that aligns with their preexisting beliefs (6–11). However, some recent scholarship questions whether the “echo chamber” narrative has been exaggerated (12, 13). Some experiments suggest that social media can indeed increase polarization. For example, temporarily deactivating Facebook can reduce polarization on policy issues (14). However, other work suggests that polarization has grown the most among older demographic groups, who are the least likely to use social media (15), albeit the most likely to vote. As such, there is an open debate about the role of social media in political polarization and intergroup conflict.Other research has examined the features of social media posts that predict “virality” online. Much of the literature focuses on the role of emotion in social media sharing. High-arousal emotions, whether they are positive (e.g., awe) or negative (e.g., anger or outrage), contribute to the sharing of content online (16–20). Tweets expressing moral and emotional content are more likely to be retweeted within online political conversations, especially by members of one’s political in-group (21, 22). On Facebook, posts by politicians that express “indignant disagreement” receive more likes and shares (23), and negative news tends to spread farther on Twitter (24). Moreover, false rumors spread farther and faster on Twitter than true ones, especially in the domain of politics, possibly because they are more likely to express emotions such as surprise and fear (25).Yet, to our knowledge, little research has investigated how social identity motives contribute to online virality. Group identities are hypersalient on social media, especially in the context of online political or moral discussions (26). For example, an analysis of Twitter accounts found that people are increasingly categorizing themselves by their political identities in their Twitter bios over time, providing a public signal of their social identity (27). Additionally, since sharing behavior is public, it can reflect self-conscious identity presentation (28, 29). According to social identity theory (30) and self-categorization theory (31), when group identities are highly salient, this can lead individuals to align themselves more with their fellow in-group members, facilitating in-group favoritism and out-group derogation in order to maintain a positive sense of group distinctiveness (32). Thus, messages that fulfill group-based identity motives may receive more engagement online. As an anecdotal example, executives at the website Buzzfeed, which specializes in creating viral content, reportedly noticed that identity-related content contributed to virality and began creating articles appealing to specific group identities (33).People may process information in a manner that is consistent with their partisan identities, prior beliefs, and motivations, a process known as motivated cognition (34–37). Scholars noted early on that the degree to which individuals identify with their political party “raises a perceptual screen through which the individual tends to see what is favorable to his [or her] partisan orientation” (38). Partisan motivations have been hypothesized to influence online behavior, such as the sharing of true and false news online (39, 40). Accordingly, we suggest that just as people engage in motivated cognition—processing information in a way that supports their beliefs—people may also engage in motivated tweeting (or sharing, liking, or retweeting), selectively interacting with and attending to content that aligns with their partisan identity motivations. There is already evidence suggesting that people selectively follow (41) and retweet (10, 42) in-group members at much higher rates than out-group members.In polarized political contexts, out-group animosity may be a more successful strategy for expressing one’s partisan identity and generating engaging content than in-group favoritism. Political polarization has been growing rapidly in the United States over the past few decades. Affective polarization, which reflects dislike of people in the opposing political party as compared to one’s own party, has most strikingly increased (43), and ideological polarization may have increased as well (though this is still a topic of debate) (44). This growth in affective polarization is driven primarily by increasing out-party animosity (rather than increasing in-party warmth)—a phenomenon known as “negative partisanship” (45). According to recently released American National Election Studies data, affective polarization grew particularly steeply from 2016 to 2020, reaching its highest point in 40 y. Out-party animosity, more so than in-party warmth, has also become a more powerful predictor of important behaviors, such as voting behavior (46) and the sharing of political fake news (39). When out-party animosity is strong, partisans are motivated to distinguish themselves from the out-party (by, for instance, holding opinions that are distinct from the out-party) (47). While some research suggests that out-group cues might be more powerful than in-group cues (48), there is still debate about the extent to which partisan belief and behavior is driven by in-group favoritism versus out-group derogation (49). A limitation of prior research is that much of it is based on self-report surveys, and so it remains unknown how expressions of in-group favoritism or out-group animosity play out in a social media context—or whether one might be a more powerful contributor to virality than the other.We investigated the role that political in-group and out-group language, as well as emotional language, play in predicting online engagement in a large sample of posts from news media accounts and US congressional members (n = 2,730,215). We sought to examine this on both Facebook and Twitter since they are two of the world’s largest and most influential social media companies and constitute around three billion users out of nearly four billion total social media users worldwide (50). Specifically, we were interested in 1) how political in-group and out-group language compared to other established predictors of social media engagement, 2) whether in-group or out-group language was a better predictor of shares and retweets, and 3) whether out-group terms were associated with negative emotions (as measured by the six Facebook “reactions”), and whether in-group terms were associated with positive emotions, reflecting patterns of out-party derogation and in-group favoritism. Finally, 4) we wanted to see if these findings applied to both news sources and political leaders, who often have an outsized influence on social discourse as well as policy change.     

La difusión del conocimiento en hepatología en tiempos de cambio o por qué deberías estar en Twitter

The ways in which information is shared, regardless of its origin, are constantly undergoing major changes. These shifts affecting how people interact and exchange knowledge have been subject to disruptive changes in recent years, due to the possibilities created by social media. The SARS-CoV-2 pandemic has exponentially accelerated these changes and innovations. In health and biomedical settings, Twitter is a key tool. This document aims to depict and describe the nascent opportunities in the field of knowledge dissemination and research on hepatology.     

Understanding Social Media: Opportunities for Cardiovascular Medicine

Cardiology professionals have used social media platforms such as Twitter to gain exposure to new research, network with experts, share opinions, and engage in scientific debates. The power of social media to communicate openly, with wide-reaching access worldwide, and at a rate faster than ever before makes it a formidable force and voice. However, evolving individual and institutional use has resulted in uncertainty for all parties on how to optimally advance this newer digital frontier. Thus, the purpose of this paper is to: 1) introduce the basics of social media usage (with the focus on Twitter); 2) provide perspective on best social media practices in academic and clinical cardiovascular medicine; and 3) present a vision for social media and the future of cardiovascular medicine.     

Social Media,Text Messaging,and Email—Preferences of Asthma Patients between 12 and 40 Years Old

Background. Electronic media such as social media (Facebook, Twitter, MySpace), email, and text messaging could be useful in the management of asthma. However, patient use and preferences for electronic media in asthma management is currently unknown. Methods. A survey was sent to asthma patients between 12–40 years of age. The survey collected demographic information, use of electronic media, interest in using electronic media to receive asthma information, and interest in using electronic media to communicate with a health care provider about asthma. Free text entries were encouraged. Results. 145 completed surveys were returned. Text messaging, email, and Facebook were used at least weekly by a majority of respondents (82%, 77%, and 65%, respectively). Email was clearly the most preferred method to receive asthma information and to communicate with a physician. There was some interest in using Facebook or text messaging, whereas Myspace and Twitter had minimal interest. On logistic regression analysis, female and Black or Hispanic participants were more likely to have an interest in the use of electronic media for asthma care. Frequent users (>1X/week) of each electronic media type had greater enthusiasm for their incorporation into asthma care. Free text entries revealed that many participants felt social media sites were for connecting with friends rather than for health care, and privacy concerns were also raised. Conclusion. Electronic media offers a novel way to improve asthma care. Email was the most preferred method, though text messaging and social media sites like Facebook may be appropriate for certain patients.     

Do age differences in close and problematic family ties reflect the pool of available relatives?

Older adults consistently report having fewer close and fewer problematic social ties than do younger adults. Yet, prior studies have not explicitly examined associations between the availability of living relatives and the nature of family ties in later life. One hundred sixty-four individuals ages 13 to 99 described their networks of close and problematic social ties. Then they provided information about specific living relatives (e.g., spouse, mother, father, sons, daughters, siblings, grandparents, and grandchildren). Older individuals reported more living relatives than did adolescents or young adults. Although individuals of all ages tended to name the majority of living relatives as close social contacts, most adults did not name all available relatives as close contacts. Age differences emerged with regard to naming relatives as problematic social ties. Older adults were less likely to indicate that their relatives caused problems. Findings are discussed in terms of an extension of investment theory, the availability hypothesis, which suggests that individuals with few living relatives are likely to view more of these relatives as close ties and fewer of these relatives as problematic.     

Size,Composition, and Strength of Ties of Personal Social Support Networks Among Adult People Living with HIV/AIDS in Henan and Beijing,China

To characterize the level of personal support available to people living with HIV/AIDS (PLWHA) in Henan and Beijing, China, face-to-face interviews were conducted to collect information on network size, composition, and strength of ties. The number of people as sources of support for participants in Henan varied from 1 to 13 and 1 to 16 in Beijing. In Henan, family members were more likely to provide support than non-relatives and they provided support more frequently; in Beijing non-relatives were more likely to provide support than family members. Family members were closer to PLWHA than non-relatives in both sites, but the closest type of relative and non-relative supporters were different between Henan and Beijing. PLWHA in Henan and Beijing receive considerable social support, but there is still opportunity for additional social support. Efforts should be made to mobilize civil society to provide support for PLWHA in China.     

Social Media as a Means to Disseminate and Advocate Cardiovascular Research: Why,How, and Best Practices

The use of Twitter or other social media platforms for research can transcend current limitations in the dissemination of research and present new opportunities for research networking by connecting researchers, clinicians, policymakers, the public, and other stakeholders on a global scale. As social media influence continues to expand, it becomes increasingly important for cardiovascular researchers to employ social media strategies to increase the impact of their research work, for the ultimate goal of improved outcomes for patients living with or at risk for cardiovascular diseases. Altmetrics are novel metrics that track the attention that scholarly outputs are receiving in non-traditional sources such as in the news, blogs, and social media posts. These alternative metrics record research dissemination beyond traditional journal citation indices, while also predicting and even promoting future citations. This review outlines various methods of how social media can be used to disseminate research, guidance on how to develop a social media portfolio for consideration of academic promotion, and some best practices for promoting one’s research work.     

Twitter conversations about food poverty: an analysis supplemented with Google Trends analysis

BackgroundAlthough the UK has not routinely collected national data on household food insecurity, the United Nations estimates that 8·4 million people in the UK experience food insecurity, a point emphasised by UN Special Rapporteur Philip Alston. With the use of novel and mixed methods we explored current topics, communications, and characteristics of social media networks on food poverty posted on Twitter. Our research questions were: what discussions were taking place on Twitter related to food poverty within the specified time? What hashtags, words, and websites were the most mentioned related to food poverty? What word-pair groups emerged by social analysis?MethodsWe used NodeXL Pro software to collect tweets sent between Nov 28 and Nov 30, 2018, using the phrase food poverty. This temporal range controlled for variables associated with food poverty, notably school-aged children and holiday periods, as we used Twitter's free public application programming interface (API) limit of 18 000 tweets and search range of 9 days. We analysed and visualised our data using social and semantic analysis tools such as overall graph metrics, vertex degree, vertex betweenness and closeness centralities, words and word pairs, and Network top items graph metrics. We also explored the spatiotemporal trends associated with this phrase using Google Trends.FindingsWe identified 4843 Twitter users whose recent tweets contained the term food poverty. There was 6039 tweets and connections in our network including 376 unique tweets, 3576 retweets, 1625 mentions, and 462 replies. The users shared information related to the existence of food poverty in the UK. Conversations included the growing numbers of foodbanks, welfare reforms, and Universal Credit as the cause of this problem. Google Trends indicated the highest degree of interest for food poverty search queries was related to New Zealand, followed by the UK and USA. Philip Alston was also the highest search term trend in the UK during this time.InterpretationThis research provides a snapshot of conversations about food poverty on Twitter. The themes we obtained indicate a lack of acknowledgment of food poverty in terms of both social policy and public health in the UK. Capturing and analysing social communications using this approach has highlighted increasing public awareness of food poverty.FundingTeesside University.     

Social support exchanges in a social media community for people living with HIV/AIDS in China

In recent years, social media has become an important source of social support. People living with HIV/AIDS in China created an online support group (the HIV/AIDS Weibo Group) on Weibo, the Chinese version of Twitter, in January 2011. The current study examined how social support transmitted in this social media community. First, messages over five successive weeks (2 May 2011 to 13 June 2011) were randomly selected from the HIV/AIDS Weibo Group on Weibo. Next, we employed social network analysis to map the HIV/AIDS Weibo Group’s structure and to measure the study variables. After that, a multivariate analysis of variance was applied to examine the influence of frequency of contact and reciprocity on informational and emotional social support exchanged in each dyad. The results revealed that pairs with a high level of contact frequency or reciprocity exchanged more informational support than do pairs with a low level of contact frequency or reciprocity. Moreover, dyadic partners with high frequency of contact exchanged a larger amount of emotional support than those with a low level frequency of contact; but strongly reciprocal dyads did not exchange significantly more emotional social support than their counterparts with a low level of reciprocity.     

Inferring social ties from geographic coincidences

We investigate the extent to which social ties between people can be inferred from co-occurrence in time and space: Given that two people have been in approximately the same geographic locale at approximately the same time, on multiple occasions, how likely are they to know each other? Furthermore, how does this likelihood depend on the spatial and temporal proximity of the co-occurrences? Such issues arise in data originating in both online and offline domains as well as settings that capture interfaces between online and offline behavior. Here we develop a framework for quantifying the answers to such questions, and we apply this framework to publicly available data from a social media site, finding that even a very small number of co-occurrences can result in a high empirical likelihood of a social tie. We then present probabilistic models showing how such large probabilities can arise from a natural model of proximity and co-occurrence in the presence of social ties. In addition to providing a method for establishing some of the first quantifiable estimates of these measures, our findings have potential privacy implications, particularly for the ways in which social structures can be inferred from public online records that capture individuals’ physical locations over time.     

Physicians, Social Media, and Conflict of Interest

Physicians and patients increasingly use social media technologies, such as Facebook, Twitter, and weblogs (blogs), both professionally and personally. Amidst recent reports of physician misbehavior online, as well as concerns about social media’s potential negative effect on trust in the medical profession, several national-level physician organizations have created professional guidelines on social media use by physicians. Missing from these guidelines is adequate attention to conflict of interest. Some guidelines do not explicitly mention conflict of interest; others recommend only disclosure. Recommending disclosure fails to appreciate the unique features of social media that make adequate disclosure difficult to accomplish. Moreover, in emphasizing disclosure alone, current guidelines are inconsistent with medicine’s general trend toward management or elimination, not just disclosure, of potential conflicts. Because social media sites typically rely on physicians’ voluntary compliance with professional norms, physicians necessarily play a major role in shaping these norms’ content and scope. To achieve the benefits of social media and ensure the veracity of social media content while preserving trust in the profession, physicians must reaffirm their commitment to disclose potential conflicts; advocate for better electronic disclosure mechanisms; and develop concrete management strategies—including, where necessary, the elimination of conflicts altogether.     

Social Media Use in Cardiovascular Imaging

Social Media is a rising influence in the global world of cardiovascular medicine, allowing for a dynamic approach to physician education, research dissemination and collaborative discussion. The visual nature of social media platforms, particularly Twitter, lends itself particularly well to the tremendous advances and stunning visuals of cardiac imaging. The hashtag “#cardiotwitter” provides around the clock, asynchronous, ubiquitous, free education. It allows connection among cardiac imagers across the world to share ideas and discuss contemporary issues pertaining to multimodality imaging. This review highlights the role of social media in advancing the practice of cardiac imaging and provides guidance on gaining visibility in the social media imaging community.     

Twitter sentiment analysis from Iran about COVID 19 vaccine

Background and aimsThe development of vaccines against COVID-19 has been a global purpose since the World Health Organization declared the pandemic. People usually use social media, especially Twitter, to transfer knowledge and beliefs on global concerns like COVID-19-vaccination, hence, Twitter is a good source for investigating public opinions. The present study aimed to assess Persian tweets to (1) analyze Iranian people's view toward COVID-19 vaccination. (2) Compare Iranian views toward a homegrown and imported COVID-19-vaccines.MethodsFirst, a total of 803278 Persian tweets were retrieved from Twitter, mentioning COVIran Barekat (the homegrown vaccine), Pfizer/BioNTech, AstraZeneca/Oxford, Moderna, and Sinopharm (imported vaccines) between April 1, 2021 and September 30, 2021. Then, we identified sentiments of retrieved tweets using a deep learning sentiment analysis model based on CNN-LSTM architecture. Finally, we investigated Iranian views toward COVID-19-vaccination.Results(1) We found a subtle difference in the number of positive sentiments toward the homegrown and foreign vaccines, and the latter had the dominant positive polarity. (2) The negative sentiment regarding homegrown and imported vaccines seems to be increasing in some months. (3) We also observed no significant differences between the percentage of overall positive and negative opinions toward vaccination amongst Iranian people.ConclusionsIt is worrisome that the negative sentiment toward homegrown and imported vaccines increases in Iran in some months. Since public healthcare agencies aim to increase the uptake of COVID-19 vaccines to end the pandemic, they can focus on social media such as Twitter to promote positive messaging and decrease opposing views.     

A Digital Ethnography of Medical Students who Use Twitter for Professional Development

BACKGROUND

While researchers have studied negative professional consequences of medical trainee social media use, little is known about how medical students informally use social media for education and career development. This knowledge may help future and current physicians succeed in the digital age.

OBJECTIVE

We aimed to explore how and why medical students use Twitter for professional development.

DESIGN

This was a digital ethnography.

PARTICIPANTS

Medical student “superusers” of Twitter participated in the study

APPROACH

The postings (“tweets”) of 31 medical student superusers were observed for 8 months (May–December 2013), and structured field notes recorded. Through purposive sampling, individual key informant interviews were conducted to explore Twitter use and values until thematic saturation was reached (ten students). Three faculty key informant interviews were also conducted. Ego network and subnetwork analysis of student key informants was performed. Qualitative analysis included inductive coding of field notes and interviews, triangulation of data, and analytic memos in an iterative process.

KEY RESULTS

Twitter served as a professional tool that supplemented the traditional medical school experience. Superusers approached their use of Twitter with purpose and were mindful of online professionalism as well as of being good Twitter citizens. Their tweets reflected a mix of personal and professional content. Student key informants had a high number of followers. The subnetwork of key informants was well-connected, showing evidence of a social network versus information network. Twitter provided value in two major domains: access and voice. Students gained access to information, to experts, to a variety of perspectives including patient and public perspectives, and to communities of support. They also gained a platform for advocacy, control of their digital footprint, and a sense of equalization within the medical hierarchy.

CONCLUSIONS

Twitter can serve as a professional tool that supplements traditional education. Students’ practices and guiding principles can serve as best practices for other students as well as faculty.

Electronic supplementary material

The online version of this article (doi:10.1007/s11606-015-3345-z) contains supplementary material, which is available to authorized users.KEY WORDS: social media, undergraduate medical education, internet, twitter, professional development