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Background: Recent years have seen a rapid growth in the number of online health communities targeted at patients with long-term conditions. Myasthenia Gravis (MG) is a rare neurological disease for which such communities have not been analysed before. The aim of this study was to better understand the needs of the MG population through the collation and categorisation of questions that users of MG social media were asking fellow users on these platforms. Methodology: Systematic observation of four MG Facebook groups was conducted over a 2-month period. Groups were selected for analysis based on the following systematic criteria: Language (English), Membership (≥ 5,000 members), group activity (≥ 2 posts per week), target audience (general MG population) and researcher engagement with group administrators. The study protocol was reviewed by the institutional review board of the Charité—Universitätsmedizin Berlin (EA2/106/22). During the observation period, data were extracted from individual posts featuring questions made across each group using a systematic and objective coding scheme. All data points were coded directly from the source and collated into an SPSS database (IBM SPSS V.27, SPSS). Absolute and relative frequencies were calculated for categorical variables and proportions were compared across groups to validate the credibility and relevance of different requests. Results: Of the 2,062 posts observed (N = 2,062), 1,392 featured questions (n = 1,392). Questions were asked by 787 unique users: 531 were identified as one-time users (67%) and 256 were identified as repeat users (33%). Six hundred and fifty six users were classified as presumed diagnosed (83%), 61 as seeking diagnosis (8%), 69 as family and/or friends (9%) and as other (<0%). Eight unique categories of questions were observed including MG treatment (31%), Symptoms (19%), Living with MG (12%), Diagnosis (10%), non-MG medication (11%), Tests (8%), Location (4%) and Other (4%). Conclusion: Members of the MG population make active use of online health communities to seek and discuss practical information concerning various aspects of the disease, its diagnosis and care. The openness and willingness of the sample population to share sensitive medical information shows a high need for information not entirely catered to by the medical profession. [ABSTRACT FROM AUTHOR]

Scholars have grown increasingly interested in the ways media and communication technologies facilitate the spread of problematic information as well as how their affordances manifest in practice. While we have learned much about the structure and use of popular social media platforms, we have more to learn about less mainstream platforms, and about the ways their usage helps actors amass and wield media power. Accordingly, this paper examines networked political actors' use of alternative media to generate capital and facilitate the spread of problematic information. Drawing data from two years of research on the pro-Trump internet forum The_Donald following its ban from Reddit, the analysis considers how users develop, debate, and deploy media-related practices, and what role those practices play in shaping the broader political culture in which they exist. In addition to gleaning insights from sustained participant-observation in the forums, a content analysis of activist meta-discourse examines the technological structure and affordances of The_Donald as well as the most salient themes and broader discursive patterns, focusing specifically on those aspects of the forum that pertain to practices of manipulation and expressions of media power. This analysis shows how the structure and culture of the forum enable and encourage manipulative media practices. Furthermore, it demonstrates how the unique combination of affordances and political opportunities available to actors allowed them to generate and wield novel forms of networked media capital. [ABSTRACT FROM AUTHOR]

Cyberbullying, a critical concern for digital safety, necessitates effective linguistic analysis tools that can navigate the complexities of language use in online spaces. To tackle this challenge, our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers (BERT) base model (cased), originally pretrained in English. This model is uniquely adapted to recognize the intricate nuances of Arabic online communication, a key aspect often overlooked in conventional cyberbullying detection methods. Our model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media (SM) tweets showing a notable increase in detection accuracy and sensitivity compared to existing methods. Experimental results on a diverse Arabic dataset collected from the 'X platform' demonstrate a notable increase in detection accuracy and sensitivity compared to existing methods. E-BERT shows a substantial improvement in performance, evidenced by an accuracy of 98.45%, precision of 99.17%, recall of 99.10%, and an F1 score of 99.14%. The proposed E-BERT not only addresses a critical gap in cyberbullying detection in Arabic online forums but also sets a precedent for applying cross-lingual pretrained models in regional language applications, offering a scalable and effective framework for enhancing online safety across Arabic-speaking communities. [ABSTRACT FROM AUTHOR]

The purpose of this qualitative descriptive study was to understand the experiences of food insecure college students during the Covid-19 pandemic. Twenty-four students who self-identified as food insecure were recruited from social media and email listservs. Individual Zoom interviews were conducted. The recordings of interviews were transcribed and analyzed. Three major themes emerged: (1) access to more resources; (2) multiple losses; and (3) "college kids need help." [ABSTRACT FROM AUTHOR]

Social Media acts as a primary source of information, opinion, and news source for millions of individuals every day for over a decade. This has never been as apparent as the global pandemic of COVID-19, wherein a span of more than just a year, the evolution of emotions amongst the users of social media has never been so swift and fickle. This study uses Reddit post-extraction and classifies 60,370 posts between the time frame of February 11th, 2020 to January 26th, 2021 from the two major subreddits of r/COVID and r/COVID19. With the help of the Lexicon Approach, the posts are classified into positive, negative, and neutral sentiment polarities, and then distributive frequencies and valence scores are measured for measuring emotional contagion. The findings reveal that there is a high presence of negative sentiments in the posts, and the increase in sentimental extremities occurred in three time-frames, the initial pandemic stage; the implementation of massive lockdowns stage; and the approval and administration of vaccines stage. It also shows that there is a linear relationship between the valence of exposed stimuli and their response. Emotional contagion is present in both positive as well as negative posts. The important implications can be drawn for the emotional wellbeing, perspective, and contagion of the users of Reddit. [ABSTRACT FROM AUTHOR]

Trypophobia is the condition in which individuals report a range of negative emotions when viewing clusters of small holes. Since the phenomenon was first described in the peer-reviewed literature a decade ago, 49 papers have appeared together with hundreds of news articles. There has also been much discussion on various Internet forums, including medical and health-related websites. In the present article, we examine the degree to which the phenomenon is caused by a form of social learning, specifically, its ubiquitous social media presence. We also examined its prevalence among the broad population. In Experiment 1 (n = 2,558), we assessed whether younger people and females (i.e., greater social media users) are more sensitive to trypophobic stimuli, as predicted by the social media hypothesis. In Experiment 2 (n = 283), we examined whether sensitivity to trypophobic stimuli and rates of trypophobia is greater in people who are aware of the condition's existence, as opposed to those who have never heard of the phenomenon. In line with the social media theory, results showed that younger people and females are indeed more susceptible to trypophobia. However, 24% of trypophobic individuals have never heard of the condition. Overall, these data suggest that both social learning and non-social learning contribute to trypophobia. We also find that the prevalence of trypophobia is approximately 10%. [ABSTRACT FROM AUTHOR]

Internet users often express their evaluation of food in online posts. This study sets out to comprehensively annotate evaluative words in food posts in Chinese, which deserves more attention due to its increasing dominance on the Internet. The corpus includes 180 posts from Dcard, currently the largest anonymous social media platform in Taiwan. All the words annotated to be evaluative are categorized according to their grammatical class, evaluative function, and subjective polarity. We not only provide the frequency distributions of the evaluative words but also conduct four case studies of high-frequency evaluative words, identifying their lexico-syntactic patterns. While previous studies on evaluative language have tended to focus on particular words/phrases, with the data mainly from English, the present study provides a more comprehensive quantitative perspective and extends to Chinese data. Moreover, because conveying evaluations in online forums can be a mediatized performance intended for attention and visibility, our qualitative analysis demonstrates how Dcard users establish readers’ involvement through evaluation. [ABSTRACT FROM AUTHOR]

This study investigates the nature and extent of moral panic (Cohen, S. (1972) 2011. Folk Devils and Moral Panics. 1st ed. Routledge) surrounding Arabic in Turkey from 1999 to 2024, using Ekşi Sözlük, a popular online forum in Turkey. All the topic titles related to Arabic within this time period (N = 1026) were compiled, yielding a corpus of 18,343 comments about Arabic. A six-phase thematic analysis (Braun, V., and V. Clarke. 2006. “Using Thematic Analysis in Psychology.” Qualitative Research in Psychology 3 (2): 77–101) revealed consistent perceptions of Arabic as a threat to Turkey’s linguistic unity, with a strong desire to limit its use. A notable increase in the instances of moral panic coincided with the rise in the Arabic-speaking population after the 2011 Syrian refugee crisis. Prevalent concerns included the use of Arabic as a sign of invasion and erosion of Turkish identity. Further analysis of 3200 comments, annotated based on whether they fuelled the panic atmosphere or resisted it, revealed a prevailing tendency among users to perpetuate the moral panic. Moral panic contexts elicited significantly more subsequent comments compared to non-moral panic contexts, as revealed by negative binomial regressions, indicating the amplifying effect of this moral panic on online discourse. The findings highlight the evolving dynamics of social control in the digital era amidst the complexities of multilingualism. [ABSTRACT FROM AUTHOR]

Mergers and acquisition is one of particularly brazen forms of controlling shareholders and managers to extract private benefits from retail investors in China. This study examines whether social media can play a positive role in impeding the opportunistic M&A actives. Using textual analysis to examine the effect of the Internet stock message board postings on M&A process, we find that retail investors' critical postings elicit negative market reaction, lower the acquisition premiums, and even make controlling shareholders and managers to withdraw the M&A attempt. Our results are consistent with the notion that social media play a role in corporate governance and the protection of retail investors' interests. [ABSTRACT FROM AUTHOR]

Introduction: Children in boarding schools spend most of their time without their parents or caregivers, causing concerns about the suitability of such schools for children with asthma. This study assessed individuals' opinions regarding the suitability of boarding secondary schools for children with asthma. Methods: A qualitative design was adopted for this study using a focus group discussion held on a social media platform (WhatsApp®) of the Asthma Awareness and Care Group (AACG), The group comprised 150 registered members. The study was guided by a structured protocol and based on a vignette comprising three questions. Data were analysed via thematic analysis using framework principles. Results: Out of the 150 eligible members, there were responses from only 19 participants. Majority of the respondents were aged ≤ 30 years (n = 17, 89.5%). The three main themes generated from the thematic analysis include the appropriateness of boarding schools for children with asthma; facilities necessary for boarding schools to cater to children with asthma; and outright rejection of children with asthma by boarding schools. Respondents conceptualised the appropriateness of boarding schools for students with asthma in six distinct sub-themes: asthma severity and extent of control, child's self-efficacy and assertiveness, child equipped with tools (knowledge, inhalers, and asthma control diary), school awareness, facilities, and active support, availability of a guardian, and the knowledge and perception of teachers and schoolmates about asthma. The sub-themes associated with the themes were presented, alongside exemplar quotes from respondents. The majority of the respondents (61.5%) were in support of allowing children with asthma attend boarding schools but with some caveats such as without liability to the school, if facilities are unavailable. Conclusion: Children's age, autonomy, asthma management status, and the school's readiness were identified as important considerations for the safe attendance of children with asthma at boarding schools. [ABSTRACT FROM AUTHOR]

Sentiment analysis (SA) is the popular natural language processing (NLP) problem utilized for analyzing texts, including uploaded reviews and user posts on e-commerce portals, forums, and social media platforms, regarding their opinions about the event or person, product, and service. The SA task comprises analyzing text to determine whether the sentiment expressed is negative, positive, or neutral, aiming for precise subjective data analysis. The deep learning (DL) technique enables various architectures to model SA tasks and has surpassed other machine learning (ML) techniques as the first method to perform SA tasks. Recent advancements in the DL model depart from the growing dominance of transformer language algorithms and convolutional neural network (CNN) and recurrent neural network (RNN) models. Utilizing pre-trained transformer language models to transfer knowledge to downstream tasks has emerged as a cutting-edge model in NLP. Therefore, the study designs a fractal walrus optimizer with self-attention DL-based SA in applied linguistics (WOSADL-SAAL) method. The WOSADL-SAAL method aims to recognize and classify the presence of sentiments in social media content. In the WOSADL-SAAL technique, data preprocessing is initially performed to transform the input dataset into a meaningful format. In addition, the WOSADL-SAAL technique uses the bag of words (BoW) model for extracting features. The self-attention bidirectional long short-term memory (SA-BiLSTM) network is applied to classify sentiment. The walrus optimizer (WO) model performs the hyperparameter tuning model to boost the detection outcomes of the SA-BiLSTM network. The performance evaluation of the WOSADL-SAAL method takes place under the benchmark SA dataset. The experimental analysis of the WOSADL-SAAL method exhibited a superior accuracy value of 99.07% and 99.24% under TUSA and IMDB datasets over existing approaches. [ABSTRACT FROM AUTHOR]

This study investigates the psychological impact of viewing user-generated content depicting extreme real-world violence. Eight threads were harvested from a publicly accessible online discussion forum in which people discussed their experiences of witnessing real-world torture, maiming or death online. Reflexive thematic analysis was used to systematically analyse these threads. The themes capture the contradictory ways in which people react to viewing extreme real-world violence online, with some finding it intensely distressing and others using it as a resource for psychological grounding or (perceived) strengthening. Based on this analysis, we highlight pathways that may lead to the cessation or continuation of viewing such content and argue that greater research on this seemingly common but under-studied experience is warranted. [ABSTRACT FROM AUTHOR]

Free Open-Access Medical Education (FOAMed) has transformed medical education in the past decade by complementing and substituting for traditional medical education when needed. The attractiveness of FOAMed resources is due to their inexpensive nature, wide availability, and user ability to access on demand across a variety of devices, making it easy to create, share, and participate. The subject of nephrology is complex, fascinating, and challenging. Traditional didactic lectures can be passive and ineffective in uncovering these difficult concepts and may need frequent revisions. Active teaching methods like flipped classrooms have shown some benefits, and these benefits can only be multifold with current social media tools. Social media will inspire the involvement of students and allow them to create and share educational content in a "trendy way," encouraging the participation of their peers and thus building an educational environment more conducive to them while promoting revision and retainment. FOAMed also promotes asynchronous learning, spaced learning, microlearning, and multimodal presentation with a meaningful variation. This article discusses the evolution of digital education, social media platforms, tools for creating and developing FOAMed resources, and digital scholarship. [ABSTRACT FROM AUTHOR]

This article explores the impact of digital platforms like TikTok and YouTube on the consumption of news and information by young people. It raises concerns about the uncurated content that is served to users through algorithms and the potential implications for society. The author argues that while there have been regulatory efforts to address competition issues in the digital world, there is still a need for regulation in the information ecosystem. The article also discusses the role of AI in content creation and distribution and its potential impact on the reliability of information. Ultimately, the article suggests that the dominance of digital gatekeepers and the lack of quality control in user-generated content pose a threat to democracy and the exchange of ideas. It proposes several ideas for regulation, including limiting personalized advertising, strengthening platform responsibility, monitoring the use of AI, breaking up information monopolies, and implementing positive regulation to ensure a certain plurality and quality of information. The author also calls on European politicians to address toxic cultures on platforms and restrict the use of the internet and social media by children and young people. [Extracted from the article]

Introduction:Use of telehealth increased during the COVID-19 pandemic and continues to be a popular health resource. This study analyzed the frequency and sentiment of telehealth discussions on Reddit. Methods:The data set included 13,071 publicly available Reddit submissions containing keywords related to telehealth over a 3-year period. We identified 173 unique subreddit communities, which were coded into mutually exclusive categories: (1) general telehealth, (2) individual care, (3) professional, (4) news, and (5) COVID-19. The Vader lexicon-based machine was used to assign sentiment scores. Results:Most subreddits were coded as individual care (n = 112), professional (n = 26), and news (n = 22). The frequency of submissions increased during the first 2 months of the pandemic and dropped in June 2020, but remained consistent through October 2022. Most Reddit submissions were positive in sentiment (56%). Conclusion:Findings show a mostly positive view of telehealth among Reddit users and an increase in telehealth-related discussions since the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Most online media consumption is not driven by a desire to seek out news and politics. However, the public may still encounter politics because it arises organically in communities devoted to non-political subjects. This study examines the potential of popular reality television online discussion forums to serve as online third spaces and stimulate political discussion due to the natural connections that audiences make between the cast members and "real life" in reality-based programming. Based on a quantitative analysis of political comments made to reality television subreddits and a survey of visitors to a popular subreddit focused on The Bachelor television show, the findings not only demonstrate the ability of entertainment-focused online communities to expose a broad segment of the public to political talk, but also point to the obstacles in promoting political discussion that is simultaneously enjoyable, informative, and tolerant of diverse viewpoints. [ABSTRACT FROM AUTHOR]

People are increasingly turning to social media and online forums like Reddit to cope with work-related concerns. Previous research suggests that how others respond can be an important determinant of the sharer's affective and wellbeing outcomes. However, less is known about whether and how cues embedded in the content of what is shared can shape the type of responses that one receives from others, obscuring the joint and interactive role that both the sharer and listener may play in influencing the sharer's outcomes. In this study, we develop theory to advance our understanding of online coping with an explicitly social focus using computational grounded theorizing and machine learning (ML) techniques applied to a large corpus of workrelated conversations on Reddit. Specifically, our theoretical model sheds light on the dynamics of the online social coping process related to the domain of work. We show that how sharers and listeners interact and react to one another depends on the content of stressors shared, the social coping behaviors used when sharing, and whether the sharer and listener belong to the same occupational context. We contribute to the social coping literature in three ways. First, we clarify how social actors respond to cues embedded in the social coping attempt. Second, we examine the moderating role that such responses play in shaping sharer outcomes. Finally, we extend theory on social coping with work-related stressors to the online domain. Taken together, this research highlights the importance of the dynamic interplay between sharer and listener in the context of online social coping. [ABSTRACT FROM AUTHOR]

Social media platforms have been adapted into society in various ways during last two decades. Few studies have examined social media content from the perspective of the individual library professional, and in particular, from librarians' social media posts about their work. This research explores social media complaints from library professionals to reveal insights into the areas of concern related to libraries as expressed in an informal, discursive style. Reddit data from three library subReddits was collected through a Python script. A total of 272 complaint posts with enough information were coded manually. A computational tool, Linguistic Inquiry and Word Count (LIWC), was also used to extract linguistic characteristics of each post. The majority of the sources of the complaint posts came from librarians (86.76%). The top five categories of the target of the complaints were patrons (27.94%), the poster's organization (20.22%), the poster's supervisor (11.03%), the library field (11.03%), and the poster's coworkers (10.29%). The top four topics of the complaint posts were patron behavior (21.69%), negative work environment (16.18%), job expectations (11.76%), and service expectations (10.66%). Organizations should put into place mechanisms and processes through which employees may share their concerns and exercise their voice, with no retribution, to solve workplace problems. [ABSTRACT FROM AUTHOR]

Does the internet facilitate everyday public deliberation? Previous research on this question has largely focused on specific aspects, such as online news media diets or political discussions on social media. However, increasingly complex media environments are composed of different arenas with different respective potential for democracy. While previous work extensively dealt with the quality of political discussion online, it is a necessary but overlooked step, to consider the upstream features of digital infrastructure and usage. Using digital trace data from Germany, this study maps out which websites are relevant for online public discourse, introduces a measure of deliberative potential along six dimensions (information, communication, participation, connectivity, inclusivity and heterogeneity), and explores different types of websites alongside high level usage patterns. Besides a class of mainstream informational hubs, a class of quality information providers that includes most established public broadcasting sites was found. A third class of niche online forums hosts political discussions among more tightly-knit online communities, supporting previous findings of incidental exposure to political content online. While the mainstream information hubs in the sample attract a much larger volume of clicks, users spend relatively more time consuming political information on quality information sites as well as on niche online forums to engage with politics online. This project takes a more holistic perspective of the diverse ecosystem of online deliberation, while presenting a first quantitative exploration of a deliberative system. [ABSTRACT FROM AUTHOR]

Professionalism has been discussed and defined in a variety of ways, including attire and other forms of self-expression. To determine athletic trainer (AT), physical therapist (PT), and athletic training or PT students' perceptions of appearance-based professionalism in the workplace and, secondly, to ascertain how perceptions differed across professions. Cross-sectional study. Web-based survey. Athletic trainers, PTs, and athletic training and PT students who were predominantly White, non-Hispanic, female, aged 30 ± 9 years, and recruited via listservs and social media. The independent variables were participant demographics. The dependent variables were self-reported perceptions of professionalism for each photo. The survey consisted of 3 sections: demographics, 8 photos of ATs or PTs with depictions of patient-provider interactions, and open-ended responses. For each photo, participants selected yes, no, or unsure regarding the photo. An open-ended response was prompted with a no or unsure selection. The participant further described the reason for that choice. Most participants determined the health care provider depicted in 7 photos appeared professional. Only 1 photo was deemed unprofessional by the professional majority. Significant differences existed between students and professionals for 5 photos. The proportion of participants who reported the photos were unprofessional differed among professions for 2 photos. From our qualitative analysis, we found 6 domains: (1) unprofessional attire and hair, (2) situation-dependent attire, (3) role confusion and health care employer or employee identification, (4) nonappearance related, (5) tattoo-related bias, and (6) rethinking after question is displayed. What is considered appropriate and professional is not concrete. Differing concepts of professionalism generated biased judgments and criticisms. Our findings should lead providers to reexamine the definition of professionalism. The past should not dictate the future, and today's social mores can help shape the definition as it should be considered in today's settings. [ABSTRACT FROM AUTHOR]

Product reviews are becoming a more popular tool for businesses and individuals when making judgements about purchases. Spammers create synthesized reviews to either promote certain items or denigrate those of rivals to make money. As a result, in recent years, both the business and research sectors have paid close attention to the detection of false opinion spam. Customers' decision-making is severely harmed by false opinion spam in service or product evaluations. It's becoming difficult to identify false opinion spam. Accordingly, the article proposed to detect deceptive opinion spam based on a hybrid deep learning technique. Initially, the model was tested using deceptive reviews gathered from several online forums. To identify deceptive reviews, many researchers at the moment create models based on a single text attribute. On the contrary, deceptive reviewers will decisively copy the wording style of legitimate evaluations while submitting reviews. These text-feature-based techniques may or may not be successful. As a result, the research suggested an ensemble multiple-feature selection technique of the Extra tree classifier to extract information based on a variety of features, including text, behaviour, and deceptive scoring features. In addition, a data resampling approach is used that integrates the Borderline-SMOTE algorithm to reduce the effects of the high dimensional imbalanced class category distribution. For detecting deceptive reviews, the article developed a hybrid technique of Bidirectional Long Short-Term Memory (Bi-LSTM) with a Capsule Neural Network to detect the positive and negative false opinions spam. The model optimizes the dynamic routing algorithm and changes the structure of the conventional capsule network without sacrificing classification performance, leading to high model accuracy. The model performance is evaluated using Python software. The study assesses the suggested model using data from two distinct domains (hotel and restaurant) as a standard benchmark. The experimental results demonstrate the advantage of neural models with higher accuracy of 99% respectively, showing that the suggested neural model greatly outperforms the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

This article discusses a cross-sectional study of Reddit discussion posts on the topic of skin bleaching and the barriers to health literacy associated with it. The authors present ultrasound findings as a noninvasive alternative to biopsy for diagnosing certain skin conditions. They also introduce a new therapeutic option, minimally invasive hair transplantation, for the treatment of nevus psiloliparus. The article emphasizes the importance of recognizing and addressing the infrequent condition of nevus psiloliparus in clinical settings. [Extracted from the article]

Introduction: As sexuality in physical education (PE) is often treated as a taboo subject, social media platforms, online chats, and internet forums are emerging as spaces where it is negotiated more openly and broadly by current and former actors of the field. This paper contributes to a better understanding of the discursive construction of sexuality in PE in such online communication. Methods: In line with The Sociology of Knowledge Approach to Discourse (SKAD) we investigate basic schemes of interpretation of sexuality with a heterogeneous sample of threads (17 threads from seven different online forums) on different PE situations in Germany. The threads are analyzed using grounded theory coding procedures. Results: Our discourse analysis reveals that the multifaceted and often controversial online discussions are structured by two dominant schemes of interpreting students' sexuality in PE, both of which are differentiated in complex ways: The online communication draws on - and by that reproduces - a nature and a culture perspective on constellations of body, sex, gender, and sexuality. We detail how from each perspective, different knowledge about these constellations, different everyday phenomena and problems in PE, and different norms for dealing with these phenomena and problems become important. Discussion: Discussing these results in the context of previous literature, we argue that it is important to address sexuality in a subject-specific approach and take the discursive knowledge and fundamental schemes of interpretation into account that shape the (im-)possibilities of addressing sexuality in PE. [ABSTRACT FROM AUTHOR]

In the digital age, social media has a significant impact on consumer perceptions. This business communication study examines the linguistic strategies used to express and repair negative electronic word of mouth (eWOM) in Hong Kong’s luxury hotel sector. The data, which were collected from travel forums, consist of 17,344 words from online hotel reviews (11,647 words) and responses (5,697 words) made by the visitors and senior hotel management of 18 five-star hotels. Using systemic functional linguistics as a framework, this study analyses the logical relations that exist between expectant and concessive conjunctions, as well as the evaluative judgment resources present in an appraisal system. The analysis focuses on the poor service standards framed in the complaints and how the hotel management responds to such situations differently, particularly with respect to repairing customer expectations. This study also examines how loyal fans and frequent travellers present their customer identity when dealing with service-related issues. By developing an understanding of how luxury hotels manage customer complaints, repair customer relationships, and protect their brand reputation through dynamic interactions, this study can provide valuable communication insights for the hotel sector. [ABSTRACT FROM AUTHOR]

Purpose Antibiotic use and misuse are common in pregnant women and young children. Few studies have assessed real-world discussions of antibiotics in these populations. Using social media posts of pregnant women and parents, our goal was to identify key themes about facilitators and barriers to appropriate antibiotic usage. Methods A purposive sample of public posts and comments relevant to antibiotic use was collected from the BabyCenter United States social media site. Using a directed content analysis, themes related to facilitators and barriers to appropriate antibiotic use were identified. Results Seven hundred and twenty-six posts and 5227 comments were analysed. Themes centred around individual factors, interpersonal factors, and structural factors. Individual factors included knowledge and beliefs. Though misinformation was present, most parents were aware of appropriate antibiotic usage and perceived antibiotics as safe and effective. Some hesitance around using antibiotics led to recommendations for home remedies or over-the-counter treatments. Interpersonal factors focused on a lack of available offline peer support, the expertise of providers, as well as a potential lack of attention from those providers. Structural factors, including access to care, also impacted parents' antibiotic use and misuse. Conclusion Though most parents demonstrated appropriate knowledge about antibiotics and a willingness to follow guidelines, negative experiences with their providers, a lack of support from peers, and structural factors presented as potential barriers to appropriate antibiotic use. Implementing avenues for peer support for parents, allowing more time for providers to address parents' concerns, and improving access to providers could improve appropriate antibiotic use in parents. [ABSTRACT FROM AUTHOR]

Entrepreneurs can benefit from the communities they build. Therefore, many entrepreneurs create online communities that allow self-selected stakeholders, such as customers, crowd investors, or enthusiasts, to interact with the venture and other like-minded individuals. However, research on how entrepreneurs can successfully engage community members and grow such online communities is only slowly emerging. In particular, it is unclear if, how much, and which content entrepreneurs should contribute to foster engagement in different types of communities and which role these community types play in the community's overall growth. Based on a longitudinal case study in the video game industry, we first theorize and show that—depending on the community type—both too much and too little entrepreneur-provided content fails to leverage community engagement potential and that different communities require more or less diverging content. We then theorize and show that community growth is largely driven by engagement in open communities, such as those hosted on social media. We outline the implications this has for entrepreneurs, our understanding of online communities, and entrepreneurial communities more generally. Plain English Summary: How can entrepreneurs engage and grow different types of online communities? Managing online communities is crucial for many entrepreneurs. However, different community types, open and core, play different roles and require different content and growth strategies. Core communities, such as those hosted on online forums, respond well to less but more diverse content, whereas open communities on social media drive overall community growth with more but less diverse content. Entrepreneurs need to find the right balance and pay attention to the tipping point of content provision, as too much content might endanger community member engagement. By understanding the dynamics of online communities, entrepreneurs can effectively nurture engagement and optimize their efforts for long-term success. Investing resources wisely in content production, considering the costs involved, can be beneficial for new ventures seeking sustainable community growth. [ABSTRACT FROM AUTHOR]

Background: As the impact of the COVID-19 pandemic winds down, both individuals and society are gradually returning to life and activities before the pandemic. This study aims to explore how people's emotions have changed from the pre-pandemic period during the pandemic to this post-emergency period and whether the sentiment level nowadays has returned to the pre-pandemic level. Method: We collected Reddit social media data in 2019 (pre-pandemic), 2020 (peak period of the pandemic), 2021, and 2022 (late stages of the pandemic, transitioning period to the post-emergency period) from the subreddits communities in 128 universities/colleges in the U.S., and a set of school-level baseline characteristics such as location, enrollment, graduation rate, selectivity, etc. We predicted two sets of sentiments from a pre-trained Robustly Optimized BERT pre-training approach (RoBERTa) and a graph attention network (GAT) that leverages both the rich semantic information and the relational information among posted messages and then applied model stacking to obtain the final sentiment classification. After obtaining the sentiment label for each message, we employed a generalized linear mixed-effects model to estimate the temporal trend in sentiment from 2019 to 2022 and how the school-level factors may affect the sentiment. Results: Compared to the year 2019, the odds of negative sentiment in years 2020, 2021, and 2022 are 25%. 7.3%, and 6.3% higher, respectively, which are all statistically significant at the 5% significance level based on the multiplicity-adjusted p-values. Conclusions: Our study findings suggest a partial recovery in the sentiment composition (negative vs. non-negative) in the post-pandemic-emergency era. The results align with common expectations and provide a detailed quantification of how sentiments have evolved from 2019 to 2022 in the sub-population represented by the sample examined in this study. [ABSTRACT FROM AUTHOR]

Forensic evaluators are increasingly called upon to review online collateral information, including social media posts, web forum posts, chat histories, and other sources such as manifestos. This information is especially vital when assessing members of a virtual community such as that of the involuntary celibate, or incel community. While this new wealth of information can add valuable context to the forensic assessment, it presents unique challenges for the evaluator including challenges with authenticity and interpretation. This article will present an approach to evaluations of such collateral, including a review of the relevant empirical research in this area and touch upon important areas to consider in the forensic evaluation of incel online activity. [ABSTRACT FROM AUTHOR]

Geolocated social media data hold a hitherto untapped potential for exploring the relationship between user mobility and their interests at a large scale. Using geolocated Twitter data from Nigeria, we provide a feasibility study that demonstrates how the linkage of (1) a trajectory analysis of Twitter users' geolocation and (2) natural language processing of Twitter users' text content can reveal information about the interests of migrants. After identifying migrants via a trajectory analysis, we train a language model to automatically detect the topics of the migrants' tweets. Biases of manual labelling are circumvented by learning community‐defined topics from a Nigerian web forum. Results suggest that differences in users' mobility correlate with varying interests in several topics, most notably religion. We find that Twitter data can be a flexible source for exploring the link between users' mobility and interests in large‐scale analyses of urban populations. The joint use of spatial techniques and text analysis enables migration researchers to (a) study migrant perspectives in greater detail than is possible with census data and (b) at a larger scale than is feasible with interviews. Thereby, it provides a valuable complement to interviews, surveys and censuses, and holds a large potential for further research. [ABSTRACT FROM AUTHOR]

Introduction: There is limited research examining the biopsychosocial impact of cyclic vomiting syndrome (CVS) on patients. This study aims to assess individuals' experiences, fears, and concerns associated with CVS and the impact of CVS on their daily lives. Methods: We employed social netnography to analyze publicly available posts related to CVS that were identified from six US online forums and Twitter. A randomly selected sub‐cohort of posts per pre‐defined criteria was first qualitatively analyzed using an inductive thematic approach. Then, machine learning topic modeling was applied to explore themes in an unsupervised manner for the entire corpus of posts. Afterward, findings from the qualitative and quantitative approaches were integrated to generate a thematic network. Results: Based on the 39,179 collected posts, seven domain themes were identified. Overall, 41.4% of the posts were related to "biopsychosocial burden" of CVS, including physical impact, psychological impact, and social impact. In 22.3% of posts, individuals shared their experience of "interactions with the healthcare system", and 14.2% of posts were related to "perceived CVS triggers." Individuals also shared "solutions to alleviate their symptoms" and "mental health needs" in 10.2% and 8.8% of posts, respectively. Finally, 6.1% of the posts were about "seeking/sharing support" with others. Discussion: This is the first social netnography study to describe the in‐depth experiences of individuals living with CVS and the marked impact on their physical, mental, and social health. The study also highlights the unmet need for effective therapies, both pharmacological and non‐pharmacological, to alleviate the biopsychosocial impact of CVS. [ABSTRACT FROM AUTHOR]

Background: Misinformation, defined as a claim that is false or misleading, considers information that is both shared with the intention of causing harm, and information that is false with no ill intent. Early attempts to downplay the risk of monkeypox (mpox) by singling out men who have sex with men (MSM) may have had the ill effect of stigmatising this group in discussions online. The aim of this study was to evaluate themes present on Instagram related to the 2022 mpox outbreak under #monkeypox. Specifically, this study sought to determine if the pervasive narratives surrounding the coronavirus disease 2019 (COVID-19) pandemic, particularly related to government mistrust and conspiracy, were penetrating discussions about mpox. Methods: A total of 255 posts under #monkeypox (the top 85 posts per day, every 10 days in July 2022) were collected on Instagram. A content analysis approach, which seeks to quantify themes present, was utilised to evaluate themes present in posts under #monkeypox. Results: Contrary to previous research investigating public health misinformation online, the majority of posts under #monkeypox were categorised as accurate information (85.9%). Moreover, a surprising number of posts were classified as anti-misinformation (32.9%), whereby users actively worked to debunk false information being shared online related to mpox. Conclusions: We hypothesise that early labelling of the disease as one that strictly affects online MSM communities has resulted in the digital community coming together to fact-check and debunk misinformation under #monkeypox on Instagram. Ever present in our digital world, misinformation continues to threaten public health efforts and, in some cases, stigmatises specific groups. Our work investigated the evolving rhetoric surrounding monkeypox (mpox) during the 2022 outbreak on Instagram, discovering that perhaps early dialogue singling out men who have sex with men shifted discussions online to combat this misinformation. By understanding the way misinformation is spread, we can better protect against it and create improved communication strategies. [ABSTRACT FROM AUTHOR]

This article focuses on culturally diverse university students' online (dis)agreement with affective expressions in English as a lingua franca (ELF). A private intercultural group on the social media site Facebook was used for the online discussions. This study analyzed online participants' comments on controversial sociopolitical issues about the TikTok ban and the Mulan boycott. Through content analyses of online responsive discourse, a range of discursive strategies used by the participants to express (dis)agreement were identified. The participants tended to give contingent (dis)agreements with mitigating expressions and supporting grounds, and the moderators frequently used reported speech, gave opposite opinions, and questioned the claims for alternative positionings. Discourse-pragmatic analyses of emoji-mediated communication also revealed creative and diverse uses of emojis and other nonverbal interactional resources in the coconstruction of humorous discourse and transformation between positive and negative affect stances. This study contributes to a deeper understanding of ELF users' pragmatic and emotive capability to participate in the online social argumentative practice of affective stance-taking. • This study explored culturally diverse university students' online (dis)agreement with affective expressions. • The participants' Facebook discussions related to controversial sociopolitical issues were analyzed. • A range of (dis)agreement and discursive strategies with emojis were identified. • Discourse-pragmatic analyses presented creative co-construction of social argumentative practices. [ABSTRACT FROM AUTHOR]

Background: The rate of suicide death has been increasing, making understanding risk factors of growing importance. While exposure to explicit suicide-related media, such as description of means in news reports or sensationalized fictional portrayal, is known to increase population suicide rates, it is not known whether prosuicide website forums, which often promote or facilitate information about fatal suicide means, are related to change in suicide deaths overall or by specific means. Objective: This study aimed to estimate the association of the frequency of Google searches of known prosuicide web forums and content with death by suicide over time in the United States, by age, sex, and means of death. Methods: National monthly Google search data for names of common prosuicide websites between January 2010 and December 2021 were extracted from Google Health Trends API (application programming interface). Suicide deaths were identified using the CDC (Centers for Disease Control and Prevention) National Vital Statistics System (NVSS), and 3 primary means of death were identified (poisoning, suffocation, and firearm). Distributed lag nonlinear models (DLNMs) were then used to estimate the lagged association between the number of Google searches on suicide mortality, stratified by age, sex, and means, and adjusted for month. Sensitivity analyses, including using autoregressive integrated moving average (ARIMA) modeling approaches, were also conducted. Results: Months in the United States in which search rates for prosuicide websites increased had more documented deaths by intentional poisoning and suffocation among both adolescents and adults. For example, the risk of poisoning suicide among youth and young adults (age 10-24 years) was 1.79 (95% CI 1.06-3.03) times higher in months with 22 searches per 10 million as compared to 0 searches. The risk of poisoning suicide among adults aged 25-64 was 1.10 (95% CI 1.03-1.16) times higher 1 month after searches reached 9 per 10 million compared with 0 searches. We also observed that increased search rates were associated with fewer youth suicide deaths by firearms with a 3-month time lag for adolescents. These models were robust to sensitivity tests. Conclusions: Although more analysis is needed, the findings are suggestive of an association between increased prosuicide website access and increased suicide deaths, specifically deaths by poisoning and suffocation. These findings emphasize the need to further investigate sites containing potentially dangerous information and their associations with deaths by suicide, as they may affect vulnerable individuals. [ABSTRACT FROM AUTHOR]

Background: Attitudes toward abortion have historically been characterized via dichotomized labels, yet research suggests that these labels do not appropriately encapsulate beliefs on abortion. Rather, contexts, circumstances, and lived experiences often shape views on abortion into more nuanced and complex perspectives. Qualitative data have also been shown to underpin belief systems regarding abortion. Social media, as a form of qualitative data, could reveal how attitudes toward abortion are communicated publicly in web-based spaces. Furthermore, in some cases, social media can also be leveraged to seek health information. Objective: This study applies natural language processing and social media mining to analyze Reddit (Reddit, Inc) forums specific to abortion, including r/Abortion (the largest subreddit about abortion) and r/AbortionDebate (a subreddit designed to discuss and debate worldviews on abortion). Our analytical pipeline intends to identify potential themes within the data and the affect from each post. Methods: We applied a neural network–based topic modeling pipeline (BERTopic) to uncover themes in the r/Abortion (n=2151) and r/AbortionDebate (n=2815) subreddits. After deriving the optimal number of topics per subreddit using an iterative coherence score calculation, we performed a sentiment analysis using the Valence Aware Dictionary and Sentiment Reasoner to assess positive, neutral, and negative affect and an emotion analysis using the Text2Emotion lexicon to identify potential emotionality per post. Differences in affect and emotion by subreddit were compared. Results: The iterative coherence score calculation revealed 10 topics for both r/Abortion (coherence=0.42) and r/AbortionDebate (coherence=0.35). Topics in the r/Abortion subreddit primarily centered on information sharing or offering a source of social support; in contrast, topics in the r/AbortionDebate subreddit centered on contextualizing shifting or evolving views on abortion across various ethical, moral, and legal domains. The average compound Valence Aware Dictionary and Sentiment Reasoner scores for the r/Abortion and r/AbortionDebate subreddits were 0.01 (SD 0.44) and −0.06 (SD 0.41), respectively. Emotionality scores were consistent across the r/Abortion and r/AbortionDebate subreddits; however, r/Abortion had a marginally higher average fear score of 0.36 (SD 0.39). Conclusions: Our findings suggest that people posting on abortion forums on Reddit are willing to share their beliefs, which manifested in diverse ways, such as sharing abortion stories including how their worldview changed, which critiques the value of dichotomized abortion identity labels, and information seeking. Notably, the style of discourse varied significantly by subreddit. r/Abortion was principally leveraged as an information and outreach source; r/AbortionDebate largely centered on debating across various legal, ethical, and moral abortion domains. Collectively, our findings suggest that abortion remains an opaque yet politically charged issue for people and that social media can be leveraged to understand views and circumstances surrounding abortion. [ABSTRACT FROM AUTHOR]

Background: To mitigate safety concerns, regulatory agencies must make informed decisions regarding drug usage and adverse drug events (ADEs). The primary pharmacovigilance data stem from spontaneous reports by health care professionals. However, underreporting poses a notable challenge within the current system. Explorations into alternative sources, including electronic patient records and social media, have been undertaken. Nevertheless, social media's potential remains largely untapped in real-world scenarios. Objective: The challenge faced by regulatory agencies in using social media is primarily attributed to the absence of suitable tools to support decision makers. An effective tool should enable access to information via a graphical user interface, presenting data in a user-friendly manner rather than in their raw form. This interface should offer various visualization options, empowering users to choose representations that best convey the data and facilitate informed decision-making. Thus, this study aims to assess the potential of integrating social media into pharmacovigilance and enhancing decision-making with this novel data source. To achieve this, our objective was to develop and assess a pipeline that processes data from the extraction of web forum posts to the generation of indicators and alerts within a visual and interactive environment. The goal was to create a user-friendly tool that enables regulatory authorities to make better-informed decisions effectively. Methods: To enhance pharmacovigilance efforts, we have devised a pipeline comprising 4 distinct modules, each independently editable, aimed at efficiently analyzing health-related French web forums. These modules were (1) web forums' posts extraction, (2) web forums' posts annotation, (3) statistics and signal detection algorithm, and (4) a graphical user interface (GUI). We showcase the efficacy of the GUI through an illustrative case study involving the introduction of the new formula of Levothyrox in France. This event led to a surge in reports to the French regulatory authority. Results: Between January 1, 2017, and February 28, 2021, a total of 2,081,296 posts were extracted from 23 French web forums. These posts contained 437,192 normalized drug-ADE couples, annotated with the Anatomical Therapeutic Chemical (ATC) Classification and Medical Dictionary for Regulatory Activities (MedDRA). The analysis of the Levothyrox new formula revealed a notable pattern. In August 2017, there was a sharp increase in posts related to this medication on social media platforms, which coincided with a substantial uptick in reports submitted by patients to the national regulatory authority during the same period. Conclusions: We demonstrated that conducting quantitative analysis using the GUI is straightforward and requires no coding. The results aligned with prior research and also offered potential insights into drug-related matters. Our hypothesis received partial confirmation because the final users were not involved in the evaluation process. Further studies, concentrating on ergonomics and the impact on professionals within regulatory agencies, are imperative for future research endeavors. We emphasized the versatility of our approach and the seamless interoperability between different modules over the performance of individual modules. Specifically, the annotation module was integrated early in the development process and could undergo substantial enhancement by leveraging contemporary techniques rooted in the Transformers architecture. Our pipeline holds potential applications in health surveillance by regulatory agencies or pharmaceutical companies, aiding in the identification of safety concerns. Moreover, it could be used by research teams for retrospective analysis of events. [ABSTRACT FROM AUTHOR]

Recently, there will be more than 4.62 billion social media users worldwide. A large number of users tend to publish personal emotional dynamics or express opinions on social media. These massive user data provide data support for the development of mental illness detection research and have achieved good results. However, it is difficult for current mental illness detection models to accurately identify key emotional features from a large number of posts issued by users to detect problem users. In view of the fact that the existing models cannot more accurately extract the words with high emotional contribution in the content of user posts, this paper proposes two hierarchical user post feature representation models, named Single-Gated LeakReLU-CNN (SGL-CNN) and Multi-Gated LeakyReLU-CNN (MGL-CNN). We leverage these 2 models to identify users with mental illness in online forums. For all posts published by each user within a certain time span, the model proposed in this paper can identify key emotional features in them and filter out other unimportant information as much as possible. In addition, the addition of gating units in this paper can significantly improve the performance of emotion detection tasks. The experimental results based on the task of RSDD dataset prove that the performance of the model proposed in this paper is superior to that of the existing methods. [ABSTRACT FROM AUTHOR]

The rise of the Internet and social media (i.e. reviews, forum discussions, blogs and social networks) constituted an interesting source to detect user opinion trends. This study examines the global publication output on opinion mining and sentiment analysis from documents published in 2000 to 2020. Bibliometric indicators on the trends, most cited papers, authors, institutions, countries, funding agencies and research subject areas were independently screened and analysed using bibliometrix package in R. A total of 7603 eligible documents were identified from 2000 to 2020. The total number of citations for all publications was 129,251, with an average of 17.0 citations per publication. About 14,629 authors wrote those documents with 1.93 authors per document and a collaboration index of 1.98. The most prolific author was Cambria Erik, with 47 publications and h-index of 42. The leading countries for research were China with n = 824, India with n = 576 and the United States with n = 244 publications. Lecture Notes in Computer Science proceedings was the top-ranked venue for publications with n = 434, h-index of 32 and 4598 total citation scores. National Natural Science Foundation of China was the top-ranked funding agency for research, and most of the publications were computer science (n = 6320) documents. The study provides an in-depth assessment of the landmark of the hot research topic and acknowledges the contribution of the most productive and active authors across different countries in the world. In addition, the findings could support the younger scholars in their future research direction and improve the efficiency in potential future research collaborations and projects. [ABSTRACT FROM AUTHOR]

The article addresses the origins of fact-checking followed by an examination of some of the challenges and opportunities facing the enterprise. Topics discussed include the emergence of fact-checking, evaluative perceptions that the public holds about the practice of fact-checking, and factors attributed to the effectiveness of fact-checking.

This study aimed to find out if there is a relationship between social media and political polarization in Türkiye from the perspective of Turkish students. To reach this aim, the needed data were collected through qualitative and quantitative approaches. A total of 303 valid questionnaires were analyzed. The sample consisted of university Turkish students across undergraduate, masters, and PhD levels in Türkiye aged between 18 and 50+. As well, an online focus group discussion with six Turkish students from different universities and education levels was conducted to gain a more in-depth understanding of the study's problem. The results of the study showed that the perspectives of the Turkish students were that social media had a weak-to-moderate effect on political polarization in Türkiye. Furthermore, the results indicated that the studied sample of the Turkish students does not rely on social media platforms to obtain political news, and most of them do not follow political leaders on social media. Moreover, communication platforms did not encourage many Turkish students to express themselves, which is an indication that social media algorithms have contributed to a medium degree in creating filter bubbles through the content they suggest to users. Results have also shown that Turkish students are afraid that their posts and comments are being censored. [ABSTRACT FROM AUTHOR]

Online social media networks have become a significant platform for persons with mental illnesses to discuss their struggles and obtain emotional and informational assistance in recent years. One such platform is Reddit, where sub-groups called 'subreddits' exist, based on a variety of topics including mental illnesses such as anxiety or depression. We analyse the user's interactions to calculate the mental health status by formulating and using a parameter called 'emotional tone' representing the user's emotional state. VADER sentiment analysis and TextBlob are used to categorise emotional tone and find distribution of emotional polarity and subjectivity of comments. For final tone prediction, RNN and State-Of-The-Art word embedding techniques are used to develop a predictive model. The resultant model provides end-to-end categorization and prediction of emotional tone. We obtain results with respect to Weighted L1 Loss that deals with extreme responses. The MODEL transcends all the baselines by at least 12.1% and the final emotional status of the authors is positive. [ABSTRACT FROM AUTHOR]