Dataset Information

A meritocratic network formation model for the rise of social media influencers.

ABSTRACT: Many of today's most used online social networks such as Instagram, YouTube, Twitter, or Twitch are based on User-Generated Content (UGC). Thanks to the integrated search engines, users of these platforms can discover and follow their peers based on the UGC and its quality. Here, we propose an untouched meritocratic approach for directed network formation, inspired by empirical evidence on Twitter data: actors continuously search for the best UGC provider. We theoretically and numerically analyze the network equilibria properties under different meeting probabilities: while featuring common real-world networks properties, e.g., scaling law or small-world effect, our model predicts that the expected in-degree follows a Zipf's law with respect to the quality ranking. Notably, the results are robust against the effect of recommendation systems mimicked through preferential attachment based meeting approaches. Our theoretical results are empirically validated against large data sets collected from Twitch, a fast-growing platform for online gamers.

SUBMITTER: Pagan N

PROVIDER: S-EPMC8633025 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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A meritocratic network formation model for the rise of social media influencers.

Pagan Nicolò N Mei Wenjun W Li Cheng C Dörfler Florian F

Nature communications 20211130 1

Many of today's most used online social networks such as Instagram, YouTube, Twitter, or Twitch are based on User-Generated Content (UGC). Thanks to the integrated search engines, users of these platforms can discover and follow their peers based on the UGC and its quality. Here, we propose an untouched meritocratic approach for directed network formation, inspired by empirical evidence on Twitter data: actors continuously search for the best UGC provider. We theoretically and numerically analyz ...[more]

PMID: 34848698

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Project description:BackgroundSocial Media Influencers (SMIs) are a fashionable way of marketing products by creating electronic word-of-mouth (e-WOM) on social media. The marketing of complementary and alternative medicines (CAMs) by SMIs is becoming increasingly popular and gaining credibility within consumers on social media platforms. Nonetheless, advising about healthcare products on social media should be examined as it is different from endorsing other kinds of commercial products. The aim of this study is to develop a model that provides the underlying mechanisms of the stimuli of SMIs on social media towards consumers' purchase intention of CAMs.MethodsThis study used best fit framework synthesis methods to develop the model. A priori theory selection was conducted by identifying a BeHEMoTh strategy (Behavior of Interest, Health context, Exclusions and Models or Theories) to systematically approach identifying relevant models and theories relative to the research aim. Further evidence derived from primary research studies that describe the behavior identified is coded against selected a priori theory to develop the model.ResultsThis study presents a novel model for understanding the purchase behavior of CAMs using SMIs as a marketing strategy. The model included two well-known theories (theory of planned behaviour theory and source credibility theory) as well as extensive existing research from a multidisciplinary perspective. The model is exclusively designed to help identify elements affecting perceived source credibility and factors that have an influence over consumers' preferences to purchase CAMs by taking into consideration SMIs' endorsements.ConclusionsThis study provides unique insights introducing new research areas to health literature and offers, new roles for healthcare professionals in this digital era by gaining new skills and competencies required to provide more credible and accurate information about CAMs. The study also highlights the new marketing era of online health-related product endorsements and recommends that policymakers and researchers carefully evaluate the impact of SMI's on the use of CAMs, as well as to regulate the content of these promotional materials.

Project description:BackgroundWhile anti-vaccine messages on social media have been studied for content, reach, and effectiveness, less is known about those who create and promote the messages. Online influencers, or 'everyday people who are influential within their online social networks', are viewed as trusted voices who are often making similar life decisions as their followers. Therefore, their experiences with and perspectives on health issues can be persuasive.MethodsWe collaborated with a formal network of online influencers to interview, using a semi-structured interview guide, vaccine hesitant influencer mothers about their views on vaccination; their process for developing health-related social media content; their motivation to promote anti-vaccine messages; and their opinions on current vaccination messaging. Prescreening ensured a diverse sample by race/ethnicity, age, education, number of children, and geographic residence. Interviews occurred by telephone, were audio recorded, and transcribed. Themes were generated independently by two coders using a deductive coding approach.ResultsWe interviewed 15 online influencer mothers from across the U.S. (average age 39 years old; all married; 13 Caucasian, 1 African American, 1 Hispanic). In some capacity, 5 of the 15 wrote about vaccination on their blog. Those who chose not to post anti-vaccine content did so for fear of alienating followers or having their platform be the site of combative discourse among readers. When researching their social media posts, the influencers did not trust mainstream sources of health information and relied on alternative sources and search engines.ImplicationsThis exploratory study interviewed influential mothers who have the ability to spread anti-vaccine messages on social media. While most do not contribute to the anti-vaccine sentiment, understanding the motivation and practices of those that do assists the public health community in better understanding the online vaccination communication environment, leading to more effective messages to counterbalance anti-vaccine content on social media.

Project description:BackgroundHistorically, pharmaceutical companies have struggled with trust and brand reputation among key stakeholders and have adopted innovative marketing strategies to reach patients directly and rebuild those relationships. Social media influencers are a popular strategy to influence younger demographics, including Generation Z and millennials. It is common for social media influencers to work in paid partnerships with brands; this is a multibillion-dollar industry. Long have patients been active in online health communities and social media platforms such as Twitter and Instagram, but in recent years, pharmaceutical marketers have noticed the power of patient persuasion and begun to leverage "patient influencers" in brand campaigns.ObjectiveThis study aimed to explore how patient influencers communicate health literacy on pharmaceutical medications on social media to their communities of followers.MethodsA total of 26 in-depth interviews were conducted with patient influencers using a snowball sampling technique. This study is part of a larger project using an interview guide that included a range of topics such as social media practices, logistics of being an influencer, considerations for brand partnerships, and views on the ethical nature of patient influencers. The constructs of the Health Belief Model were used in this study's data analysis: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy. This study was approved by the institutional review board of the University of Colorado and adhered to ethical standards in interview practice.ResultsAs patient influencers are a new phenomenon, it was our goal to identify how health literacy on prescription medications and pharmaceuticals is being communicated on social media. Using the constructs of the Health Belief Model to guide the analysis, 3 themes were identified: understanding disease through experience, staying informed on the science or field, and suggesting that physicians know best.ConclusionsPatients are actively exchanging health information on social media channels and connecting with other patients who share similar diagnoses. Patient influencers share their knowledge and experience in efforts to help other patients learn about disease self-management and improve their quality of life. Similar to traditional direct-to-consumer advertising, the phenomenon of patient influencers raises ethical questions that need more investigation. In a way, patient influencers are health education agents who may also share prescription medication or pharmaceutical information. They can break down complex health information based on expertise and experience and mitigate the loneliness and isolation that other patients may feel without the support of a community.

Dataset Information

A meritocratic network formation model for the rise of social media influencers.

Publications

A meritocratic network formation model for the rise of social media influencers.

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