Social Media Discourse Research Articles

(263) Evaluating Changes in Social Media Discussions Regarding Vasectomies Before and After The Dobbs V. Jackson Supreme Court Decision

Abstract Introduction In June 2022, the U.S. Supreme Court overruled Roe v. Wade, the 1973 case establishing a federally protected right to abortion, through the case Dobbs v. Jackson. Subsequent research has demonstrated an increase in the number of men seeking vasectomy consultations as men take more ownership of family planning. We hypothesized that there might be a similar, paralleled change in online discussions about vasectomy following the court’s decision. Objective We sought to characterize themes and tones in social media discussions regarding vasectomies before and after the Dobbs decision. Methods We analyzed vasectomy-related discussions on Reddit, a large social media platform, using qualitative analysis and natural language processing-based sentiment analysis. Using the Reddit API, 1000 posts from 1 year before Dobbs and 1 year after were extracted from the subreddit group r/vasectomy. The group has 13,400 active members. Qualitative analysis was performed to determine overall themes within discussion posts. Poster age and comments about male sexual dysfunction were noted. Sentiment analysis was performed using the validated software VADER, which is specifically tuned expressions on social media platforms and assigns posts scores that can be interpreted as having positive, neutral, or negative sentiments. Results 213 total posts (107 pre-Dobbs and 106 post-Dobbs) were randomly selected for thematic and sentiment analysis. Posters in the post-Dobbs period were significantly younger than posters in the pre-Dobbs period (25.5 years vs. 31.7 years, p = 0.05). Posters in the post-Dobbs period were also more likely to mention their sexual dysfunction or raise questions regarding their sexual function post-operatively (p = 0.03). Notable discussion themes pre-Dobbs focused on post-operative concerns (n = 31), actionable advice (n = 38), or second opinions (n = 50). Patients also sought to reflect upon their experiences with their vasectomy (n = 30). While similar themes were noted post-Dobbs, more posts focused on describing pre-operative anxieties (n = 36), raising second thoughts regarding a scheduled vasectomy (n = 36), and acknowledging in some way the importance or value of having an online community such as r/vasectomy (n = 60). There was no significant difference in the length of posts (p = 0.44) or the number of positive, neutral, or negative sentiment posts (p = 0.98) between time periods. Conclusions Online discussion forums may provide insight into patients’ experiences with vasectomies during a contentious sociopolitical time when contraceptive options are changing. After the Dobbs decision, patients seemed to express increased pre-operative anxiety and doubt regarding their decisions to get vasectomies, but also expressed greater appreciation for the online community in r/vasectomy. This overall mix of feelings may explain any lack of difference in positive and negative sentiment in posts between the time periods. Disclosure No.

Sentiment analysis and implementation in film evaluation utilizing BERT

This study explores the use of the dmsc_v2 dataset, which is a rich collection of over 2 million ratings and commentary data from over 700,000 users on 28 films, to train the BERT model for sentiment analysis. This expansive dataset, drawn from the popular Chinese movie-rating website, Douban, has been meticulously curated for this research. In the context of the methodology, it is comprehensive and involves multiple stages. Initially, data preprocessing is conducted to refine and format the dataset suitably for model training. Subsequently, the BERT model is trained using the prepared data. Following the training process, the model's performance is critically evaluated to validate its efficacy and accuracy. The resulting model is adept at performing sentiment classification on comments pertaining to films across various social media platforms such as Weibo, Xiaohongshu, and more. This is particularly beneficial as it enables a nuanced analysis of user opinions and trending topics, offering invaluable insights for businesses, movie producers, or marketers. The findings of this study demonstrate that the BERT sentiment analysis model, developed with the dmsc_v2 dataset, exhibits impressive performance and has expansive potential for application within the sphere of social media commentary analysis. The successful development and validation of this model underscore its potential to transform the way sentiment analysis is conducted, especially in the context of entertainment and social media discussions.

Graduation Resources in News Discourse: Calls for the British Museum to Return Chinese Cultural Artefacts

Using a discourse approach, this study examines online news and opinion pieces about calls for the British Museum to return Chinese artefacts. We examine the interpersonal meanings conveyed by the linguistic choices made in these texts. This study uses the appraisal system in the systemic functional linguistic (SFL) framework to examine how news discourse addresses the issue and constructs interpersonal meanings. Graduation resources, as a subcategory of appraisal system, can underpin the degree of meanings and perspectives, allowing writers to adjust the gradability of attitudinal meanings conveyed to readers. This research first examines how the writer’s voice is embedded in graduation resources, and later, how these graduation resources are used in online news articles calling for the return of the artefacts. This study also examines how online newspapers covered a short film by vloggers called “Escape from the British Museum”, which sparked massive social media reactions, offering new perspectives on how social media and traditional news organisations interact to construct meanings through language. The results show that quantification and fulfilment (completion) resources are the two most common subcategories of graduation resources. The findings shed light on the language strategies used in news and social media discourse, as well as the interpersonal meanings behind such requests for cultural heritage repatriation.

A quantitative analysis of Twitter ("X") trends in the discussion of rhinoplasty.

Rhinoplasty is one of the most common cosmetic surgical procedures performed globally. Twitter, also known as "X," is used by both patients and physicians and has been studied as a useful tool for analyzing trends in healthcare. The public social media discourse of rhinoplasty has not been previously reported in the field of otolaryngology. The goal of this study was to characterize the most common user type, sentiment, and temporal trends in the discussion of rhinoplasty on Twitter to guide facial plastic surgeons in their clinical and social media practices. A total of 1,427,015 tweets published from 2015 to 2020 containing the keywords "rhinoplasty" or "nose job" were extracted using Twitter Academic API. Tweets were standardized and filtered for spam and duplication. Natural language processing (NLP) algorithms and data visualization techniques were applied to characterize tweets. Significantly more "nose job" tweets (80.8%) were published compared with "rhinoplasty" (19.2%). Annual tweet frequency increased over the 5 years, with "rhinoplasty" tweets peaking in January and "nose job" tweets peaking in the summer and winter months. Most "rhinoplasty" tweets were linked to a surgeon or medical practice source, while most "nose job" tweets were from isolated laypersons. While discussion was positive in sentiment overall (M = +0.08), "nose job" tweets had lower average sentiment scores (P < .001) and over twice the proportion of negative tweets. The top 20 most prolific accounts contributed to 14,758 (10.6%) of total "rhinoplasty" tweets. Exactly 90% (18/20) of those accounts linked to non-academic surgeons compared with 10% (2/20) linked to academic surgeons. Rhinoplasty-related posts on Twitter were cumulatively positive in sentiment and tweet volume is steadily increasing over time, especially during popular holiday months. The search term "nose job" yields significantly more results than "rhinoplasty," and is the preferred term of non-healthcare users. We found a large digital contribution from surgeons and medical practices, particularly in the non-academic and private practice sector, utilizing Twitter for promotional purposes.

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis.

Since September 2020, the National Health Service (NHS) COVID-19 contact-tracing app has been used to mitigate the spread of COVID-19 in the United Kingdom. Since its launch, this app has been a part of the discussion regarding the perceived social agency of decision-making algorithms. On the social media website Twitter, a plethora of views about the app have been found but only analyzed for sentiment and topic trajectories thus far, leaving the perceived social agency of the app underexplored. We aimed to examine the discussion of social agency in social media public discourse regarding algorithm-operated decisions, particularly when the artificial intelligence agency responsible for specific information systems is not openly disclosed in an example such as the COVID-19 contact-tracing app. To do this, we analyzed the presentation of the NHS COVID-19 App on Twitter, focusing on the portrayal of social agency and the impact of its deployment on society. We also aimed to discover what the presentation of social agents communicates about the perceived responsibility of the app. Using corpus linguistics and critical discourse analysis, underpinned by social actor representation, we used the link between grammatical and social agency and analyzed a corpus of 118,316 tweets from September 2020 to July 2021 to see whether the app was portrayed as a social actor. We found that active presentations of the app-seen mainly through personalization and agency metaphor-dominated the discourse. The app was presented as a social actor in 96% of the cases considered and grew in proportion to passive presentations over time. These active presentations showed the app to be a social actor in 5 main ways: informing, instructing, providing permission, disrupting, and functioning. We found a small number of occasions on which the app was presented passively through backgrounding and exclusion. Twitter users presented the NHS COVID-19 App as an active social actor with a clear sense of social agency. The study also revealed that Twitter users perceived the app as responsible for their welfare, particularly when it provided instructions or permission, and this perception remained consistent throughout the discourse, particularly during significant events. Overall, this study contributes to understanding how social agency is discussed in social media discourse related to algorithmic-operated decisions This research offers valuable insights into public perceptions of decision-making digital contact-tracing health care technologies and their perceptions on the web, which, even in a postpandemic world, may shed light on how the public might respond to forthcoming interventions.

Exploring the facilitators and barriers to addressing social media's impact on anxiety within primary care: a qualitative study.

Several researchers and policymakers have acknowledged the alarming association between social media (SM) usage and anxiety symptoms in young adults. While primary care holds a crucial role in the improvement of health outcomes for those presenting with anxiety, there has been no research on GPs' perceptions of the impact of SM on anxiety. Furthermore, there has been little discussion of SM as a risk factor in anxiety-related consultations. This study is the first to use empirical research to inform how primary care can adapt to address SM's impact on anxiety within young adults. To identify the facilitators and barriers within primary care to addressing SM's impact on anxiety among young adults. A qualitative study of GPs in the UK. Following an exploratory pilot interview, semi-structured interviews with GPs (n = 7) were transcribed and thematically analysed, following an inductive approach. The following six facilitators were identified: a framework to facilitate discussion; open GP attitudes; GP training; referral pathways; larger stakeholder influence; and young adult education of social media's impact on anxiety. The following three barriers were identified: a lack of GP awareness of SM's impact on anxiety; cautious GP attitudes; and increased pressure on the health service. This qualitative study revealed a diversity of perceptions, and these novel findings are instructive in the adaptation of primary care services to meet the current mental health needs of young adults, as well as better assisting GPs in engaging in these conversations, especially within university practice.

Benzodiazepine Boom: Tracking Etizolam, Pyrazolam, and Flubromazepam from Pre-UK Psychoactive Act 2016 to Present Using Analytical and Social Listening Techniques.

The designer benzodiazepine (DBZD) market continues to expand whilst evading regulatory controls. The widespread adoption of social media by pro-drug use communities encourages positive discussions around DBZD use/misuse, driving demand. This research addresses the evolution of three popular DBZDs, etizolam (E), flubromazepam (F), and pyrazolam (P), available on the drug market for over a decade, comparing the quantitative chemical analyses of tablet samples, purchased from the internet prior to the implementation of the Psychoactive Substances Act UK 2016, with the thematic netnographic analyses of social media content. Drug samples were purchased from the internet in early 2016. The characterisation of all drug batches were performed using UHPLC-MS and supported with 1H NMR. In addition, netnographic studies across the platforms X (formerly Twitter) and Reddit, between 2016-2023, were conducted. The latter was supported by both manual and artificial intelligence (AI)-driven thematic analyses, using numerous.ai and ChatGPT, of social media threads and discussions. UHPLC-MS confirmed the expected drug in every sample, showing remarkable inter/intra batch variability across all batches (E = 13.8 ± 0.6 to 24.7 ± 0.9 mg; F = 4.0 ± 0.2 to 23.5 ± 0.8 mg; P = 5.2 ± 0.2 to 11.5 ± 0.4 mg). 1H NMR could not confirm etizolam as a lone compound in any etizolam batch. Thematic analyses showed etizolam dominated social media discussions (59% of all posts), with 24.2% of posts involving sale/purchase and 17.8% detailing new administration trends/poly-drug use scenarios. Artificial intelligence confirmed three of the top five trends identified manually. Purity variability identified across all tested samples emphasises the increased potential health risks associated with DBZD consumption. We propose the global DBZD market is exacerbated by surface web social media discussions, recorded across X and Reddit. Despite the appearance of newer analogues, these three DBZDs remain prevalent and popularised. Reporting themes on harm/effects and new developments in poly-drug use trends, demand for DBZDs continues to grow, despite their potent nature and potential risk to life. It is proposed that greater controls and constant live monitoring of social media user content is warranted to drive active regulation strategies and targeted, effective, harm reduction strategies.

Retrograde Cricopharyngeal Dysfunction: A Review.

Retrograde cricopharyngeal dysfunction (RCPD), also referred to as retrograde cricopharyngeus dysfunction, is a condition characterized by the inability to burp. The pathophysiology of this condition is thought to result from failure of cricopharyngeal sphincter relaxation during periods of esophageal distension, which leads to patients' bothersome symptoms. RCPD negatively impacts patients' quality of life and is associated with bloating, gurgling, avoidance of carbonation, self-imposed dietary and lifestyle changes designed to minimize discomfort, and flatulence. Complaints often start during adolescence, and many patients search for a diagnosis for years before obtaining treatment. A recent increase in awareness through patient-led social media discussion boards describing the 'no burp' syndrome is leading to an increasing incidence of presentations, often with patients making a self-diagnosis. The increased incidence of RCPD is fueling a larger case series investigating treatment options and outcomes. In this review, we discuss what is known about the pathophysiology of this condition, the otolaryngologic perspective on diagnosis and treatment, the patients' lived experience of this condition, and the influence of social media on RCPD.

Multidimensional sentiment analysis method on social media data: comparison of emotions during and after the COVID-19 pandemic

PurposeThis study aims to elucidate the dynamics of social media discourse during global health events, specifically investigating how users across different platforms perceive, react to and engage with information concerning such crises.Design/methodology/approachA mixed-method approach was employed, combining both quantitative and qualitative data collection. Initially, thematic analysis was applied to a data set of social media posts across four major platforms over a 12-month period. This was followed by sentiment analysis to discern the predominant emotions embedded within these communications. Statistical tools were used to validate findings, ensuring robustness in the results.FindingsThe results showcased discernible thematic and emotional disparities across platforms. While some platforms leaned toward factual information dissemination, others were rife with user sentiments, anecdotes and personal experiences. Overall, a global sense of concern was evident, but the ways in which this concern manifested varied significantly between platforms.Research limitations/implicationsThe primary limitation is the potential non-representativeness of the sample, as only four major social media platforms were considered. Future studies might expand the scope to include emerging platforms or non-English language platforms. Additionally, the rapidly evolving nature of social media discourse implies that findings might be time-bound, necessitating periodic follow-up studies.Practical implicationsUnderstanding the nature of discourse on various platforms can guide health organizations, policymakers and communicators in tailoring their messages. Recognizing where factual information is required, versus where sentiment and personal stories resonate, can enhance the efficacy of public health communication strategies.Social implicationsThe study underscores the societal reliance on social media for information during crises. Recognizing the different ways in which communities engage with, and are influenced by, platform-specific discourse can help in fostering a more informed and empathetic society, better equipped to handle global challenges.Originality/valueThis research is among the first to offer a comprehensive, cross-platform analysis of social media discourse during a global health event. By comparing user engagement across platforms, it provides unique insights into the multifaceted nature of public sentiment and information dissemination during crises.

Passing on the “whistle”: Users’ creative engagement with platform censorship in an online relay campaign in China

The advances and proliferation of social media technologies have not only empowered Chinese users with more opportunities for opinion expression and public participation, but also provided the censors with increasingly sophisticated means to monitor and control the public discourse. In this game of cat and mouse, Chinese censors and users are intertwined with each other as new forms of censorship and counter-censorship stimulate both sides to further develop tactics to compete with each other. Drawing on (social) media discourse analysis, this study examines the strategies users adopted in an online relay campaign to keep a censored article alive on WeChat Public Accounts. The analysis highlights three major forms of creative strategies including textual reproductions, multi-semiotic and multimodal reproductions, and technically encoded forms. It also underscores platform censorship as a particular level of censorship where the platform takes responsibility for removing sensitive or perceived sensitive posts and content. This study adds to the growing literature that examines creative strategies of censorship engagement and a more nuanced understanding of the multi-layered online censorship mechanism in China.

From Bag-of-Words to Transformers: A Comparative Study for Text Classification in Healthcare Discussions in Social Media

From Bag-of-Words to Transformers: A Comparative Study for Text Classification in Healthcare Discussions in Social Media

Exploring Human-Centricity in Industry 5.0: Empirical Insights from a Social Media Discourse

The transition from Industry 4.0 towards Industry 5.0 marks a paradigm shift, emphasising human-centricity in industrial settings. Industry 5.0 focuses on improving the future role of people in addition to merely technological progress. While "human centricity" gains recognition, ambiguity surrounds its definition and application. The literature lacks clear consensus on the concept and its industrial implications. This paper provides clarity on human-centricity by analysing viewpoints and public opinions based on posts published on LinkedIn in the last five years regarding human-centricity. The analysis involved text mining techniques, including semantic clustering to discover distinct clusters of discussions related to human-centricity and keywords extraction to tag the different clusters. The findings reveal that public opinion predominantly centres on the skills required by future workers, encompassing both hard and soft skills, as well as social themes such as gender equity and workplace comfort. This research underscores the critical relevance of these components in the transition towards Industry 5.0, offering valuable insights for industrial practitioners and researchers alike.

Sexual Violence and Social Media Discourse: Exploring Campus Climate Through the Lens of Twitter.

Sexual violence is prevalent on college campuses, yet formal disclosure and open dialogue are often muffled. Social media has become a powerful platform for survivors and presents an opportunity for researchers to explore social discourse surrounding sexual violence on campuses. Healthcare providers must be knowledgeable of campus climate surrounding sexual violence to provide patient-centered, trauma-informed care and mitigate the detrimental, long-term effects experienced by survivors. Twitter, a social media and networking platform, was used to explore online discourse regarding sexual violence among college students. A conventional qualitative content analysis was implemented using two coders to explore data before identifying themes. The researchers identified 175 tweets that met the inclusion criteria. Three subthemes emerged: (a) lack of support, (b) powerlessness, and (c) victim blaming and shaming, which built the foundation for the overarching theme of rape culture. Social media posts provide insight into survivor experiences and offer forensic nurses and healthcare providers the opportunity to discover information that survivors might not otherwise disclose. Forensic nurses should consider implementing innovative approaches to engage campus survivors and increase access to postassault care.

Discourse Analysis of Social Media Discourse: Construction and Deconstruction of Social Reality

With social media’s rise and widespread application, social science research has entered a new era, bringing new challenges and opportunities to the academic community on how to use social media data for high-quality social reality construction and deconstruction research. Based on the dynamic evolution of social media development, this study constructs a theoretical framework for social media discourse analysis, aiming to explain the social reality construction and development mechanism jointly generated by user- generated content (UGC) and algorithmic recommendation systems in terms of discourse dissemination mechanism and information circulation mechanism. The core goal of social media development is to provide information services that meet user expectations, while committed to continuously improving user experience quality and enhancing user satisfaction. To achieve this goal, we have proposed a series of measures, such as strengthening information control based on the internal circulation of content quality, building an interactive mechanism between users and platform quality perception, and establishing an evaluation system for user feedback and platform governance to achieve high-quality development of social media, promote the construction and deconstruction of social reality, and truly meet user needs.

Sentiment analysis of subcutaneous and intravenous immunoglobulin therapy: public healthcare perception through social media discourse.

Immunoglobulin replacement therapy remains a cornerstone of treatment in antibody deficiencies and other inborn errors of immunity. While patient preferences between subcutaneous and intravenous immunoglobulin have been studied through questionnaires, no study has yet explored patient perspectives in a free environment. Therefore, we aimed to conduct a sentiment analysis as well as a temporal and geographical analysis on public opinions obtained from social media to better understand patient satisfaction and public perception on immunoglobulin therapy. A dataset of 43,700 tweets spanning from the 1st of January of 2012 to the 31st of December of 2022 was obtained. A Valence Aware Dictionary for Sentiment Reasoning sentiment analysis was performed, followed by statistical, geographical and temporal analyses. Mean polarity of intravenous immunoglobulin related tweets was 0.1295 (positive), while mean polarity for subcutaneous immunoglobulin was 0.2117 (positive). Temporal analysis through a statistical model demonstrated that the volume of tweets increased over time for both subcutaneous and intravenous treatment. Geographical analysis revealed that the majority of texts originated from the United States. The highest mean polarity was observed in Romania with a mean value of 0.2966, while the lowest polarity was documented in Norway with a mean of -0.0211. Tweets linked to subcutaneous immunoglobulin treatment had a higher average polarity, indicating a more positive public perception. The amount of tweets relating to both therapies showed a tendency to increase as the years progressed, implying an increase in public discussion on immunoglobulin treatment.

Examining media's coverage of COVID-19 vaccines and social media sentiments on vaccine manufacturers' stock prices.

The COVID-19 pandemic caused a widespread public health and financial crisis. The rapid vaccine development generated extensive discussions in both mainstream and social media, sparking optimism in the global financial markets. This study aims to explore the key themes from mainstream media's coverage of COVID-19 vaccines on Facebook and examine how public interactions and responses on Facebook to mainstream media's posts are associated with daily stock prices and trade volume of major vaccine manufacturers. We obtained mainstream media's coverage of COVID-19 vaccines and major vaccine manufacturers on Facebook from CrowdTangle, a public insights tool owned and operated by Facebook, as well as the corresponding trade volume and daily closing prices from January 2020 to December 2021. Structural topic modelling was used to analyze social media posts while regression analysis was conducted to determine the impact of Facebook reactions on stock prices and trade volume. 10 diverse topics ranging from vaccine trials and their politicization (note: check that we use American spelling throughout), to stock market discussions were found to evolve over the pandemic. Although Facebook reactions were not consistently associated with vaccine manufacturers' stock prices, 'Haha' and 'Angry' reactions showed the strongest association with stock price fluctuations. In comparison, social media reactions had little observable impact on trading volume. Topics generated reflect both actual events during vaccine development as well as its political and economic impact. The topics generated in this study reflect both the actual events surrounding vaccine development and its broader political and economic impact. While we anticipated a stronger correlation, our findings suggest a limited relationship between emotional reactions on Facebook and vaccine manufacturers' stock prices and trading volume. We also discussed potential technical enhancements for future studies, including the integration of large language models.

How social memory works on social media: A methodological framework

Abstract Social media challenge several established concepts of memory research. In particular, the day-to-day mundane discourse of social media blur the essential distinction between commemorative and non-commemorative memory. We address these challenges by presenting a methodological framework that explores the dynamics of social memory on various social media. Our method combines top-down data mining with a bottom-up analysis tailored to each platform. We demonstrate the application of our approach by studying how the Holocaust is remembered in different corpora, including a dataset of 5.3 million Facebook posts and comments collected between 2015 and 2017 and a 5 million Tweets and Retweets dataset collected in 2021. We first identify the mnemonic agents initiating the discussion of the memory of the Holocaust and those responding to it. Second, we compare the macro-rhythms of Holocaust discourse on the two platforms, identifying peaks and mundane discussions that extend beyond commemorative occasions. Third, we identify distinctive language and cultural norms specific to the memorialization of the Holocaust on each platform. We conceptualize these dynamics as ‘Mnemonic Markers’ and discuss them as potential pathways for memory researchers who wish to explore the unique memory dynamics afforded by social media.

ALGORITMO DE APRENDIZAGEM PROFUNDA COMPREENSIVA PARA COMPREENDER O PAPEL DAS REDES SOCIAIS NA PERCEPÇÃO DO CONSUMIDOR EM RELAÇÃO AO CONSUMO SUSTENTÁVEL

ABSTRACT This research proposes a comprehensive deep-learning algorithm to understand the role of social media in consumer perception of green consumption. After the COVID-19 pandemic, society has shown increased focus on the relationship between people and nature. Achieving sustainable development goals requires promoting green consumption, which necessitates understanding and influencing public attitudes toward sustainability. While previous studies have explored green consumption using behavioral models and surveys, they often overlook the perspective of social media. This study uses deep learning techniques to analyze social media data, including text and video content, to gain insights into consumer behavior and preferences. The study entails collecting data from X (former Twitter) and YouTube, developing deep learning algorithms for text classification, and creating a visualization and reporting system. More specifically, this study aims to analyze the impact of social media information sharing on society’s green purchasing intentions and proposes advanced architectures for text mining specifically the LDA method. This study highlights the valuable insights from analyzing social media discourse on green consumption. Trends, emotional attitudes, and engagement were examined using text mining and sentiment analysis. The study reveals platform-specific differences in sentiment and identifies influential keywords and phrases. The analysis also uncovers emotional responses and key factors associated with the discourse on green consumption. The findings can inform future strategies for promoting sustainable consumption. The study concludes by emphasizing the importance of further research to explore the discrepancies between platforms and harness the implications of these findings for sustainable consumption strategies.

Deciphering Influence on Social Media: A Comparative Analysis of Influential Account Detection Metrics in the Context of Tobacco Promotion

Influencer marketing spending in the United States was expected to surpass $6 billion in 2023. This marketing tactic poses a public health threat, as research suggests it has been utilized to undercut decades of public health progress—such as gains made against tobacco use among adolescents. Public health and public opinion researchers need practical tools to capture influential accounts on social media. Utilizing X (formerly Twitter) little cigar and cigarillo (LCC) data, we compared seven influential account detection metrics to help clarify our understanding of the functions of existing metrics and the nature of social media discussion of tobacco products. Results indicate that existing influential account detection metrics are non-harmonic and time-sensitive, capturing distinctly different users and categorically different user types. Our results also reveal that these metrics capture distinctly different conversations among influential social media accounts. Our findings suggest that public health and public opinion researchers hoping to conduct analyses of influential social media accounts need to understand each metric’s benefits and limitations and utilize more than one influential account detection metric to increase the likelihood of producing valid and reliable research.

Theater of Triumph and Transgression: ­Religious Discourse on Hospitality/­Hostility in the Viral Communication during the Pandemic

The present article is the outcome of the research project on religious discourse in social media (socmed) during the COVID-19 pandemic. The research focuses on the concept of hospitality and hostility, through which a welcoming, along with hostile and unfriendly attitude are displayed by netizens toward other people, to understand the nature of social relationships over digital platforms. The research employs Social Network Analysis (SNA) and Social Media Analysis to explore and visualize viral communication on Twitter, Facebook, and Instagram. The framework is viral communication as condensed sequences of actions revolving around controversial topics. Several topics under scrutiny, among others, are klepon Islami, Hagia Sophia, and Pope Francis’ controversies. Jacques Derrida mainly informs the discourse of hospitality/hostility. The result demonstrated the sporadic vulnerability of traditional understanding of hospitality. It appeared in the presence of information arbiters as communication actors, taking the middle position and mediating controversial topics. The employment of SNA in dealing with interpersonal virtues in social media is promising, as it demonstrates its mechanism and making in a specific communication context. It allows for a deeper understanding and exploration of the theory of mediatization.