scholarly journals Tailoring in the digital era: Stimulating dialogues on health topics in collaboration with social media influencers

2019 ◽  
Vol 5 ◽  
pp. 205520761882152 ◽  
Author(s):  
Roel O Lutkenhaus ◽  
Jeroen Jansz ◽  
Martine PA Bouman

In today’s media landscape, audiences increasingly turn to online communities for media consumption and to exchange information about specific niche interests such as health-related topics. This calls for a segmented approach in which interventions are targeted at online communities, tailored to their specific cultures and health-related perceptions, and leverage the dynamics of conversation and social influence in online networks. Strategies drawn from the field of influencer marketing provide interesting opportunities to reach and engage with audiences in a personally relevant manner, including with those who may disagree with an intervention’s message. This article reflects on what health communicators might learn from influencer strategies and proposes digital methods to target and tailor health communication in the digital era. More concretely, we present methods to: (a) identify online communities engaging on a specific health issue; (b) map community specific cultures and health-related perceptions; and (c) identify influencers as potential collaboration partners. As such, we adopt a slightly different take on tailoring by putting the creative and cultural competences of social influencers central, and by aligning our methods with a media mapping protocol to create influencer strategies that are tailored to the cultures and health-related perceptions of multiple online audience segments. We illustrate the potential of these methods with a study of how vaccination is discussed among Dutch Twitter users.

2021 ◽  
Vol 66 (Special Issue) ◽  
pp. 133-133
Author(s):  
Regina Mueller ◽  
◽  
Sebastian Laacke ◽  
Georg Schomerus ◽  
Sabine Salloch ◽  
...  

"Artificial Intelligence (AI) systems are increasingly being developed and various applications are already used in medical practice. This development promises improvements in prediction, diagnostics and treatment decisions. As one example, in the field of psychiatry, AI systems can already successfully detect markers of mental disorders such as depression. By using data from social media (e.g. Instagram or Twitter), users who are at risk of mental disorders can be identified. This potential of AI-based depression detectors (AIDD) opens chances, such as quick and inexpensive diagnoses, but also leads to ethical challenges especially regarding users’ autonomy. The focus of the presentation is on autonomy-related ethical implications of AI systems using social media data to identify users with a high risk of suffering from depression. First, technical examples and potential usage scenarios of AIDD are introduced. Second, it is demonstrated that the traditional concept of patient autonomy according to Beauchamp and Childress does not fully account for the ethical implications associated with AIDD. Third, an extended concept of “Health-Related Digital Autonomy” (HRDA) is presented. Conceptual aspects and normative criteria of HRDA are discussed. As a result, HRDA covers the elusive area between social media users and patients. "


2017 ◽  
Vol 12 (3) ◽  
pp. 162
Author(s):  
Elizabeth Margaret Stovold

A Review of: Swab, M., & Romme, K. (2016). Scholarly sharing via Twitter: #icanhazpdf requests for health sciences literature. Journal of the Canadian Health Libraries Association, 37(1), 6-11. http://dx.doi.org/10.5596/c16-009 Abstract Objective – To analyze article sharing requests for health sciences literature on Twitter, received through the #icanhazpdf protocol. Design – Social media content analysis. Setting – Twitter. Subjects – 302 tweets requesting health sciences articles with the #icanhazpdf tag. Methods – The authors used a subscription service called RowFeeder to collect public tweets posted with the hashtag #icanhazpdf between February and April 2015. Rowfeeder recorded the Twitter user name, location, date and time, URL, and content of the tweet. The authors excluded all retweets and then each reviewed one of two sets. They recorded the geographic region and affiliation of the requestor, whether the tweet was a request or comment, type of material requested, how the item was identified, and if the subject of the request was health or non-health. Health requests were further classified using the Scopus subject category of the journal. A journal could be classified with more than one category. Any uncertainties during the coding process were resolved by both authors reviewing the tweet and reaching a consensus. Main results – After excluding all the retweets and comments, 1079 tweets were coded as heath or non-health related. A final set of 302 health related requests were further analyzed. Almost all the requests were for journal articles (99%, n=300). The highest-ranking subject was medicine (64.9%, n=196), and the lowest was dentistry (0.3%, n=1). The most common article identifier was a link to the publisher’s website (50%, n=152), followed by a link to the PubMed record (22%, n=67). Articles were also identified by citation information (11%, n=32), DOI (5%, n=14), a direct request to an individual (3%, n=9), another method (2%, n=6), or multiple identifiers (7%, n=22). The majority of requests originated from the UK and Ireland (29.1%, n=88), the United States (26.5%, n=80), and the rest of Europe (19.2%, n=58. Many requests came from people with affiliations to an academic institution (45%, n=136). These included librarians (3.3%, n=10), students (13.6%, n=41), and academics (28.1%, n=85). When tweets of unknown affiliation were excluded (n=117), over 70% of the requests were from people with academic links. Other requesters included journalists, clinicians, non-profit organisations, patients, and industry employees. The authors examined comments in the tweets to gain some understanding of the reasons for seeking articles through #icanhazpdf, although this was not the primary focus of their study. A preliminary examination of the comments suggested that users value the ease, convenience, and the ability to connect with other researchers that social media offers. Conclusion – The authors concluded that the number of requests for health sciences literature through this channel is modest, but health librarians should be aware of #icanhazpdf as another method through which their users might seek to obtain articles. The authors recommend further research into the reasons why users sometimes choose social media over the library to obtain articles.


2020 ◽  
Vol 12 ◽  
pp. 184797901989974 ◽  
Author(s):  
Ahmad Adnan Al-Tit ◽  
Anis Omri ◽  
Tarek Bel Hadj

This study investigates the driving factors of the social commerce intention of online communities in Saudi Arabia by building a model that comprises two exogenous variables (social support and social commerce constructs (SCCs)), a mediating variable (trust), and one endogenous variable (social commerce intention). The study population comprises Facebook and Twitter users in the kingdom. A convenience sample of 500 social media users was chosen. Data were gathered via a questionnaire-based online survey. Our findings indicate that social support had a significant relationship with trust and social commerce intention. This relationship was significantly mediated by trust. SCCs also had a significant relationship with emotional as well as informational support and social commerce intention. Unexpectedly, the relationship between SCCs and social support dimensions was significantly mediated by trust. Consequently, it was concluded that social support, trust, and SCCs are key drivers of social commerce intention. These results invite social media retailers to consider such factors to increase social media users’ intention to purchase.


JAMIA Open ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Yuan-Chi Yang ◽  
Mohammed Ali Al-Garadi ◽  
Jennifer S Love ◽  
Jeanmarie Perrone ◽  
Abeed Sarker

Abstract Objective Biomedical research involving social media data is gradually moving from population-level to targeted, cohort-level data analysis. Though crucial for biomedical studies, social media user’s demographic information (eg, gender) is often not explicitly known from profiles. Here, we present an automatic gender classification system for social media and we illustrate how gender information can be incorporated into a social media-based health-related study. Materials and Methods We used a large Twitter dataset composed of public, gender-labeled users (Dataset-1) for training and evaluating the gender detection pipeline. We experimented with machine learning algorithms including support vector machines (SVMs) and deep-learning models, and public packages including M3. We considered users’ information including profile and tweets for classification. We also developed a meta-classifier ensemble that strategically uses the predicted scores from the classifiers. We then applied the best-performing pipeline to Twitter users who have self-reported nonmedical use of prescription medications (Dataset-2) to assess the system’s utility. Results and Discussion We collected 67 181 and 176 683 users for Dataset-1 and Dataset-2, respectively. A meta-classifier involving SVM and M3 performed the best (Dataset-1 accuracy: 94.4% [95% confidence interval: 94.0–94.8%]; Dataset-2: 94.4% [95% confidence interval: 92.0–96.6%]). Including automatically classified information in the analyses of Dataset-2 revealed gender-specific trends—proportions of females closely resemble data from the National Survey of Drug Use and Health 2018 (tranquilizers: 0.50 vs 0.50; stimulants: 0.50 vs 0.45), and the overdose Emergency Room Visit due to Opioids by Nationwide Emergency Department Sample (pain relievers: 0.38 vs 0.37). Conclusion Our publicly available, automated gender detection pipeline may aid cohort-specific social media data analyses (https://bitbucket.org/sarkerlab/gender-detection-for-public).


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
D Rosenberg ◽  
R Mano ◽  
G Mesch

Abstract Gender and ethnic inequalities in searching for health information have been studied extensively in the context of the internet as a whole, but rarely with respect to social media. Moreover, locality size has rarely been considered as a determinant in the search for health information. Furthermore, little attention has been paid to differences between searching for health information in general and for information on specific health issues. This study proposes a gethnic diversification approach to understand these phenomena. This approach maintains that the triple disadvantage of belonging simultaneously to three disadvantaged groups is translated into an advantage with respect to the probability of searching for health information online. The sample consisted of social media users in Israel (N = 803). The study's outcomes variables were general types of health information (medical vs. non-medical) and searching for specific health issues. The results of logistic regression analyses provide support for the gethnic diversification approach. These results imply that disadvantaged minorities residing in small localities (but also in large ones) use social media to search for health information to a greater extent than their counterparts from larger localities and than members of the advantaged group in order to compensate for their restricted amount of health-related social capital. This finding signals a major need for accessible and quality health services in small localities where many disadvantaged minority groups reside. Key messages Minority women residing in small localities should be treaten as a special group by the public health officials. More resources should be invested in developing health services in localities populated by minorities.


2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Meagan Marie Daoust

The healthcare trend of parental refusal or delay of childhood vaccinations will be investigated through a complex Cynefin Framework component in an economic and educational context, allowing patterns to emerge that suggest recommendations of change for the RN role and healthcare system. As a major contributing factor adding complexity to this trend, social media is heavily used for health related knowledge, making it is difficult to determine which information is most trustworthy. Missed opportunities for immunization can result, leading to economic and health consequences for the healthcare system and population. Through analysis of the powerful impact social media has on this evolving trend and public health, an upstream recommendation for RNs to respond with is to utilize reliable social media to the parents’ advantage within practice. The healthcare system should focus on incorporating vaccine-related education into existing programs and classes offered to parents, and implementing new vaccine classes for the public.


2016 ◽  
Vol 1 (2) ◽  
pp. 133-144
Author(s):  
Nadya Nadya

Technological developments have significantly changed the way how a business works, especially the culinary business named Seblak Jeletet Murni, that has located in Jakarta. This business is still relatively new, but consumers continue moldy and this spicy culinary product sales have been continue to increase. This phenomenon is a result of business which has entered the digital era in social media. Marketing of this product is not done intensively by the owner of this business, but consumers who moved to market virally in social media, especially social media video youtube. In this article the author analyzed descriptively about consumer behavior in digital marketing that has affected the sales of the culinary products. The analyzes were performed with case studies and associated in the literature on consumer behavior and digital marketing strategies. This article aims to describe the behavior of consumers in the digital age so that it can be input in determining the marketing strategy culinary efforts forward and be used for thought on the future of consumer research. Keywords: Digital Marketing, Social Media, Consumer Behavior


Humaniora ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 13
Author(s):  
Abitassha Az Zahra ◽  
Eko Priyo Purnomo ◽  
Aulia Nur Kasiwi

The research aimed to explain the pattern of social communication on the issue of rejection of the PLTU Batang development policy. It used data on Twitter accounts involved in the rejection of the PLTU Batang development policy. In analyzing existing data, qualitative methods and social analysis networks were used. To see social networks in the rejection of the PLTU Batang development policy, the research used the NodeXL application to find out the patterns of social communication networks in #TolakPLTUBatang. From the results, it can be seen that in the dissemination of social networking information, the @praditya_wibby account is the most central account in the social network and has a strong influence on the social network. The @praditya_wibby account has a role in moving the community through Twitter to make a critical social movement. This means that in the current digital era, democracy enters a new form through the movement of public opinion delivery through social media. Besides, by encouraging the role of online news, the distribution of information becomes faster to form new perceptions of an issue. This is evident from the correlation network where the @praditya_wibby account has correlations with several compass online media accounts, tirto.id, okezonenews, vice, antaranews, BBCIndonesia, and CNN Indonesia.


2018 ◽  
Author(s):  
Albert Moreira ◽  
Raul Alonso-Calvo ◽  
Alberto Muñoz ◽  
Jose Crespo

BACKGROUND Internet and Social media is an enormous source of information. Health Social Networks and online collaborative environments enable users to create shared content that afterwards can be discussed. While social media discussions for health related matters constitute a potential source of knowledge, characterizing the relevance of participations from different users is a challenging task. OBJECTIVE The aim of this paper is to present a methodology designed for quantifying relevant information provided by different participants in clinical online discussions. METHODS A set of key indicators for different aspects of clinical conversations and specific clinical contributions within a discussion have been defined. These indicators make use of biomedical knowledge extraction based on standard terminologies and ontologies. These indicators allow measuring the relevance of information of each participant of the clinical conversation. RESULTS Proposed indicators have been applied to two discussions extracted from PatientsLikeMe, as well as to two real clinical cases from the Sanar collaborative discussion system. Results obtained from indicators in the tested cases have been compared with clinical expert opinions to check indicators validity. CONCLUSIONS The methodology has been successfully used for describing participant interactions in real clinical cases belonging to a collaborative clinical case discussion tool and from a conversation from a Health Social Network.


2020 ◽  
Author(s):  
Aleksandra Urman ◽  
Stefania Ionescu ◽  
David Garcia ◽  
Anikó Hannák

BACKGROUND Since the beginning of the COVID-19 pandemic, scientists have been willing to share their results quickly to speed up the development of potential treatments and/or a vaccine. At the same time, traditional peer-review-based publication systems are not always able to process new research promptly. This has contributed to a surge in the number of medical preprints published since January 2020. In the absence of a vaccine, preventative measures such as social distancing are most helpful in slowing the spread of COVID-19. Their effectiveness can be undermined if the public does not comply with them. Hence, public discourse can have a direct effect on the progression of the pandemic. Research shows that social media discussions on COVID-19 are driven mainly by the findings from preprints, not peer-reviewed papers, highlighting the need to examine the ways medical preprints are shared and discussed online. OBJECTIVE We examine the patterns of medRxiv preprint sharing on Twitter to establish (1) whether the number of tweets linking to medRxiv increased with the advent of the COVID-19 pandemic; (2) which medical preprints were mentioned on Twitter most often; (3) whether medRxiv sharing patterns on Twitter exhibit political partisanship; (4) whether the discourse surrounding medical preprints among Twitter users has changed throughout the pandemic. METHODS The analysis is based on tweets (n=557,405) containing links to medRxriv preprint repository that were posted between the creation of the repository in June 2019 and June 2020. The study relies on a combination of statistical techniques and text analysis methods. RESULTS Since January 2020, the number of tweets linking to medRxiv has increased drastically, peaking in April 2020 with a subsequent cool-down. Before the pandemic, preprints were shared predominantly by users we identify as medical professionals and scientists. After January 2020, other users, including politically-engaged ones, have started increasingly tweeting about medRxiv. Our findings indicate a political divide in sharing patterns of the top-10 most-tweeted preprints. All of them were shared more frequently by users who describe themselves as Republicans than by users who describe themselves as Democrats. Finally, we observe a change in the discourse around medRxiv preprints. Pre-pandemic tweets linking to them were predominantly using the word “preprint”. In February 2020 “preprint” was taken over by the word “study”. Our analysis suggests this change is at least partially driven by politically-engaged users. Widely shared medical preprints can have a direct effect on the public discourse around COVID-19, which in turn can affect the societies’ willingness to comply with preventative measures. This calls for an increased responsibility when dealing with medical preprints from all parties involved: scientists, preprint repositories, media, politicians, and social media companies. CONCLUSIONS Widely shared medical preprints can have a direct effect on the public discourse around COVID-19, which in turn can affect the societies’ willingness to comply with preventative measures. This calls for an increased responsibility when dealing with medical preprints from all parties involved: scientists, preprint repositories, media, politicians, and social media companies.


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