Finding Users' Voice on Social Media: An Investigation of Online Support Groups for Autism-Affected Users on Facebook

Autistic discussion forums: insights into the topics that clinicians don't know about

Background

User-led autism discussion forums provide a wealth of information about autistic lived experiences, albeit oriented toward those who regularly use computers. We contend that healthcare professionals should read autism discussion forums to gain insight, be informed, and in some cases, to correct assumptions about autistic persons' lives and possibilities. But experts may be dismissive of user-led forums, believing forums to be filled with myths, misinformation, and combative postings. The questions motivating our research were: Do online forums raise issues that are educational for clinicians and other stakeholders? Are forums useful for those who do empirical research?

Method

Content analysis was conducted on 300 posts (62,000 words) from Reddit, Quora, and Wrong Planet. Forums were sampled to reflect broad topics; posts were selected sequentially from the identified forums. The authors read through posts in the Excel sheet, highlighting statements that were the main ideas of the post, to discern both broad categories of topics and more specific topics. We coded content pertinent to classic autism myths and analyzed attitudes towards myths such as 'lack emotion' and 'cannot form relationships.' To document whether forum posts discuss topics that are not widely known outside of elite experts, we compared discussion content to new material about autism contained in the March 2022 DSM 5 Text revision.

Results

Classic autism myths were discussed with examples of when elements of myths may be valid. Posters described cases where parents or therapists believed myths. Experts may believe autism myths due to rapid changes in diagnostic practices and due to their lack of knowledge regarding the characteristics of autistic people who have typical intellectual abilities. We conclude that forums contain high-value information for clinicians because all concepts in the DSM 5 text revision were discussed by posters in the years before the text revision appeared. Ideas that are only slowly becoming part of the research literature are discussed at length in forums. Reading and analyzing forums is useful for both clinicians and scientists. In addition, the relative ease of forum analysis lowers the bar for entry into the research process.

Identity and Discourse Among #ActuallyAutistic Twitter Users With Motor Differences

Despite a growing awareness of the prevalence of motor differences in the autistic community, their functional impact is poorly understood. Social media offers the ideal setting to observe this discourse in a less-contrived setting than lab-based structured interviews. The aims of the present study were (a) to determine the proportion of Twitter users who self-identify as autistic and dyspraxic/having developmental coordination disorder, relative to autistic alone, and (b) to identify common themes emerging from two moderated chat threads with motor-related prompts. Using the Twitter research application programming interface, we harvested data from users' public profiles and tweets containing terms related to autism and developmental coordination disorder within a 1-month time period. We also harvested data from two #AutChat threads related to motor skills, which included 151 tweets from 31 unique autistic users (two with co-occurring developmental coordination disorder). Of these tweets, 44 were explicitly about motor differences, while the remainder consisted of discussion topics more loosely associated with motor skills. The following common themes were quantified: manual dexterity, lower extremity, oral motor, gross motor, posture, balance, stimming, movement pain, and coordination. Together, these findings indicate that motor differences are highly recognized and discussed among autistic individuals but are not overtly integrated into their identities at the same rate.

Digital trends in autism: a scoping review exploring coverage of autism across YouTube, Twitter, and Facebook

Autism continues to be a leading neurodevelopmental disorder across adult and pediatric populations that transcends racial, ethnic, age, and socioeconomic groups worldwide. Autism care and treatment also exerts immense costs on the healthcare system and lost productivity which are partly attributed to the existing resource limitations globally. Organizations, campaigns, and policies exist worldwide in increasing equity and accessibility of resources and services to individuals with autism. In the context of our digital era, a wealth of information is also more readily available on autism through electronic communication including social media platforms. As YouTube, Twitter and Facebook are ever-growing and among the leading social media platforms in contemporary times, examination of content covered on autism across these communication mediums is timely and warranted. This review consolidates findings from 32 sources on the sources, formats, and nature of content covered on YouTube, Twitter, and Facebook pertaining to a wealth of dimensions surrounding autism. Strengths and limitations of the studies and endeavors are presented. Implications for future campaign development, health equity, health policy, neurodiversity, and patient care are also delineated. Lastly, recommendations for future research and practice are discussed which present directions for tapping into the potential of YouTube, Twitter, and Facebook as health communication mediums across the ever-changing autism landscape.

Public concerns and attitudes towards autism on Chinese social media based on K-means algorithm

To investigate the hot topics and attitudes of autism in the larger community. In this study, we analyzed and summarized experimental texts from the social media platform Zhihu using the TF-IDF algorithm and K-means clustering approach. Based on the analysis of the 1,740,826-word experimental text, we found that the popularity of autism has steadily risen over recent years. Sufferers and their parents primarily discuss autism. The K-means clustering algorithm revealed that the most popular topics are divided into four categories: self-experience of individuals with autism, external views of individuals with autism, caring and stressful behaviors of caregivers, and information about autism. This study concluded that people with autism face more incredible negative emotions, external cognitive evaluations of the autistic group reflect stereotypes, the caregiver's family suffers high financial and psychological stress, and disorders caused by disease in autistic individuals.

Socialization, Education, and Learning for the Internet (SELFI): A Pilot RCT of a Social Media Skills Group Program for Autistic Adults

Many autistic adults report preference for computer-mediated communication and social media use. Despite many benefits to online socialization, there are many challenges including anxiety and cyber-victimization. To date, support is limited related to helping autistic adults with safe and effective internet use. The purpose of this study was to evaluate the feasibility, acceptability, and preliminary efficacy of the novel SELFI program. This pilot study utilized a randomized controlled trial design. A total of 25 autistic adults enrolled in the study and were randomized to the nine-week SELFI program or a waitlist control condition. Feasibility assessed enrollment, attrition, and fidelity of delivery. Acceptability examined attendance and feedback from participants and peer mentors. Efficacy evaluated change in Facebook activity, social media utility/anxiety, and individualized goals. Regarding feasibility, the recruitment goal was met within one month, there was limited attrition, and therapists delivered the program with high fidelity. Participants attended a majority of scheduled sessions and feedback from participants reflected high levels of agreement with several facets of the program. Compared to the control group, more participants assigned to the SELFI condition were perceived by autistic and non-autistic raters as having improved Facebook activity. SELFI participants also reported reduced difficulty meeting their individualized goal. Findings support the piloted SELFI program as feasible and acceptable with signals of preliminary efficacy. This study establishes an exciting foundation regarding an innovative social media skills program, however more research is necessary.

Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic

Social media is not only an essential platform for the dissemination of public health-related information, but also an important channel for people to communicate during the COVID-19 pandemic. However, social bots can interfere with the social media topics that humans follow. We analyzed and visualized Twitter data during the prevalence of the Wuhan lab leak theory and discovered that 29% of the accounts participating in the discussion were social bots. We found evidence that social bots play an essential mediating role in communication networks. Although human accounts have a more direct influence on the information diffusion network, social bots have a more indirect influence. Unverified social bot accounts retweet more, and through multiple levels of diffusion, humans are vulnerable to messages manipulated by bots, driving the spread of unverified messages across social media. These findings show that limiting the use of social bots might be an effective method to minimize the spread of conspiracy theories and hate speech online.

For autistic persons by autistic persons: Acceptability of a structured peer support service according to key stakeholders

INTRODUCTION

Social support is a protective factor in the mental health of autistic people. Furthermore, prejudice regarding autistic people is a constraint for the development of social support programmes by autistic peers.

METHODS

The objective of this study is to describe the anticipated acceptability of structured peer support programmes for and by autistic persons. Fifteen key stakeholders (six autistic adults, four caregivers and five service providers) participated in in-depth semistructured interviews. A qualitative thematic analysis of the content of the verbatim was carried out.

FINDINGS

We found that while a structured peer social support programme is acceptable to autistic people and caregivers, there was no consensus among service providers. The latter expressed doubts about the ability of autistic people to offer support. The framing of discussions between peers, the training of peer helpers, the support for autistic leadership and an organization that considers the communicational and sensory characteristics of autistic persons, could influence adherence to such a programme. Moreover, a space without service providers is an important condition for the acceptability of a peer support programme.

CONCLUSION

A structured peer support service for and by autistic persons could be an innovative way to answer the unmet support needs of autistic people. It seems essential to anticipate potential barriers and facilitators and to communicate among health professionals to promote this approach and reduce possible prejudice about the ability of autistic people to offer support to their peers. More studies are necessary.

PATIENT OR PUBLIC CONTRIBUTION

Fifteen key stakeholders who are involved in autistic people's trajectory of service and support participated in this research. We are a research team composed of healthcare professionals and researchers, in addition to one member of our team being an autistic advocate and a mental health peer-support mentor. Two members of our team are also parents of autistic children. The comprehensibility of the questions for the interview was consulted and discussed with one autistic advocate-collaborator.

Exploring public attitudes toward live-streaming fitness in China: A sentiment and content analysis of China's social media Weibo

Objectives

Live-streaming fitness is perceived by the Chinese government as an invaluable means to reduce the prevalence of physical inactivity amid the COVID-19 pandemic. This study aims to investigate the public altitudes of the Chinese people toward live-streaming fitness and provide future health communication strategies on the public promotion of live-streaming fitness accordingly.

Methods

This study collected live-streaming fitness-related microblog posts from July 2021 to June 2022 in Weibo, the Chinese equivalent to Twitter. We used the BiLSTM-CNN model to carry out the sentiment analysis, and the structured topic modeling (STM) method to conduct content analysis.

Results

This study extracted 114,397 live-streaming fitness-related Weibo posts. Over 80% of the Weibo posts were positive during the period of the study, and over 85% were positive in half of the period. This study finds 8 topics through content analysis, which are fitness during quarantine; cost reduction; online community; celebrity effect; Industry; fitness injuries; live commerce and Zero Covid strategy.

Conclusions

It is discovered that the public attitudes toward live-streaming fitness were largely positive. Topics related to celebrity effect (5-11%), fitness injuries (8-16%), live commerce (5-9%) and Zero Covid strategy (16-26%) showed upward trends in negative views of the Chinese people. Specific health communication strategy suggestions are given to target each of the negative topics.

Parents' Use of Social Media as a Health Information Source for Their Children: A Scoping Review

BACKGROUND

Parents are increasingly using social media to inform health decisions for their children.

OBJECTIVE

This scoping review examines 1) How do parents use social media to find health information for their children? 2) What motivates parents to engage with social media to seek health information for their children? 3) How do parents seek to understand and evaluate the health information they find on social media, and how does social media impact parental health information-seeking?

METHODS

Scopus, CINAHL, Medline, PubMed, and Embase databases were searched, with open date parameters. Peer-reviewed studies that examined parents' and responsible caregivers' use of social media as a source of health information for their children (aged <18 years) were included.

RESULTS

The 42 included studies spanned 2011 to 2020. More than half (n = 24, 57%) were published in 2019 and 2020. Parents use social media for information about specific health concerns both before and after a medical diagnosis for their child. Parents are motivated to engage with social media as they seek out extensive information based on lived experience from other parents, as well as social support and community.

CONCLUSION

This scoping review reveals parents' motivation to use social media for health information, and how that can interact with, and impose on, clinical practice. It is important for those who provide pediatric health care to both understand and accommodate this permanent shift facilitated by social media, when working with parents who are seeking health information when making health decisions for their children.

Predictive Fraud Analysis Applying the Fraud Triangle Theory through Data Mining Techniques

Fraud is increasingly common, and so are the losses caused by this phenomenon. There is, thus, an essential economic incentive to study this problem, particularly fraud prevention. One barrier complicating the research in this direction is the lack of public data sets that embed fraudulent activities. In addition, although efforts have been made to detect fraud using machine learning, such actions have not considered the component of human behavior when detecting fraud. We propose a mechanism to detect potential fraud by analyzing human behavior within a data set in this work. This approach combines a predefined topic model and a supervised classifier to generate an alert from the possible fraud-related text. Potential fraud would be detected based on a model built from such a classifier. As a result of this work, a synthetic fraud-related data set is made. Four topics associated with the vertices of the fraud triangle theory are unveiled when assessing different topic modeling techniques. After benchmarking topic modeling techniques and supervised and deep learning classifiers, we find that LDA, random forest, and CNN have the best performance in this scenario. The results of our work suggest that our approach is feasible in practice since several such models obtain an average AUC higher than 0.8. Namely, the fraud triangle theory combined with topic modeling and linear classifiers could provide a promising framework for predictive fraud analysis.

Do Informational and Emotional Elements Differ between Online Psychological and Physiological Disease Communities in China? A Comparative Study of Depression and Diabetes

Disease-specific online health communities provide a convenient and common platform for patients to share experiences, change information, provide and receive social support. This study aimed to compare differences between online psychological and physiological disease communities in topics, sentiment, participation, and emotional contagion patterns using multiple methods as well as to discuss how to satisfy the users' different informational and emotional needs. We chose the online depression and diabetes communities on the Baidu Tieba platform as the data source. Topic modeling and theme coding were employed to analyze discussion preferences for various topic categories. Sentiment analysis was used to identify the sentiment polarity of each post and comment. The social network was used to represent the users' interaction and emotional flows to discover the differences in participation and emotional contagion patterns between psychological and physiological disease communities. The results revealed that people affected by depression focused more on their symptoms and social relationships, while people affected by diabetes were more likely to discuss treatment and self-management behavior. In the depression community, there were obvious interveners spreading positive emotions and more core users in the negative emotional contagion network. In the diabetes community, emotional contagion was less prevalent and core users in positive and negative emotional contagion networks were basically the same. The study reveals insights into the differences between online psychological and physiological disease communities, providing a greater understanding of the users' informational and emotional needs expressed online. These results are helpful for society to provide actual medical assistance and deploy health interventions based on disease types.

Understanding patterns of COVID infodemic: A systematic and pragmatic approach to curb fake news

Amid the flood of fake news on Coronavirus disease of 2019 (COVID-19), now referred to as COVID-19 infodemic, it is critical to understand the nature and characteristics of COVID-19 infodemic since it not only results in altered individual perception and behavior shift such as irrational preventative actions but also presents imminent threat to the public safety and health. In this study, we build on First Amendment theory, integrate text and network analytics and deploy a three-pronged approach to develop a deeper understanding of COVID-19 infodemic. The first prong uses Latent Direchlet Allocation (LDA) to identify topics and key themes that emerge in COVID-19 fake and real news. The second prong compares and contrasts different emotions in fake and real news. The third prong uses network analytics to understand various network-oriented characteristics embedded in the COVID-19 real and fake news such as page rank algorithms, betweenness centrality, eccentricity and closeness centrality. This study carries important implications for building next generation trustworthy technology by providing strong guidance for the design and development of fake news detection and recommendation systems for coping with COVID-19 infodemic. Additionally, based on our findings, we provide actionable system focused guidelines for dealing with immediate and long-term threats from COVID-19 infodemic.

Effect of Employee-Customer Interaction Quality on Customers' Prohibitive Voice Behaviors: Mediating Roles of Customer Trust and Identification

Given that customer voice behaviors are confused with customer complaint behaviors in usage, this study thoroughly explains the essential differences between the two constructs. On that basis, this study investigates how employee-customer interaction (ECI) quality affects customers' prohibitive voice behaviors, which is an crucial type of customer voice behaviors, by examining customer trust and identification as mediators. Data from 395 restaurant customers are collected and analyzed using structural equation modeling. Results show that ECI quality positively affects customers' prohibitive voice behaviors. In this effect, customer trust and identification play direct and sequential mediating roles. This study contributes theoretically to the current knowledge by clearly distinguishing customer voice behaviors from customer complaint behaviors and by providing new insights into the mechanism of customers' prohibitive voice behaviors from the perspectives of service interaction and relational benefit enhancement. The practical implications of this study can help pointedly foster customers' prohibitive voice behaviors.

Mining Early Life Risk and Resiliency Factors and Their Influences in Human Populations from PubMed: A Machine Learning Approach to Discover DOHaD Evidence

The Developmental Origins of Health and Disease (DOHaD) framework aims to understand how early life exposures shape lifecycle health. To date, no comprehensive list of these exposures and their interactions has been developed, which limits our ability to predict trajectories of risk and resiliency in humans. To address this gap, we developed a model that uses text-mining, machine learning, and natural language processing approaches to automate search, data extraction, and content analysis from DOHaD-related research articles available in PubMed. Our first model captured 2469 articles, which were subsequently categorised into topics based on word frequencies within the titles and abstracts. A manual screening validated 848 of these as relevant, which were used to develop a revised model that finally captured 2098 articles that largely fell under the most prominently researched domains related to our specific DOHaD focus. The articles were clustered according to latent topic extraction, and 23 experts in the field independently labelled the perceived topics. Consensus analysis on this labelling yielded mostly from fair to substantial agreement, which demonstrates that automated models can be developed to successfully retrieve and classify research literature, as a first step to gather evidence related to DOHaD risk and resilience factors that influence later life human health.

Social media mining in drug development-Fundamentals and use cases

The incorporation of patients' perspectives into drug discovery and development has become critically important from the viewpoint of accounting for modern-day business dynamics. There is a trend among patients to narrate their disease experiences on social media. The insights gained by analyzing the data pertaining to such social-media posts could be leveraged to support patient-centered drug development. Manual analysis of these data is nearly impossible, but artificial intelligence enables automated and cost-effective processing, also referred as social media mining (SMM). This paper discusses the fundamental SMM methods along with several relevant drug-development use cases.

Digital dermatoses: skin disorders engendered by social media in tweens and teens

PURPOSE OF REVIEW

Photograph-based social media use among children and adolescents has skyrocketed over the past decade, raising concerns about the implications for self-confidence and behavior in this population. Social media 'challenges' encourage participants to complete potentially dangerous tasks while sharing their completion of the tasks on social media. Many of these challenges affect the skin and lead to recognizable findings on physical examination. This review discusses the history of prominent social media challenges and their effects on the skin. Attention is also given to the effects of social media trends on self-confidence and body image in children and adolescents.

RECENT FINDINGS

Over the past several years, there have been several notable social media trends that can harm the skin. These include the Kylie Jenner lip challenge, salt and ice challenge, deodorant challenge, eraser challenge, fire challenge, and hot water challenge. Participation in these challenges can cause morbidity in children and adolescent that should be recognized by clinicians.

SUMMARY

Social media has become an important platform for communication and self-expression among children and adolescents. Pediatricians should remain aware of social trends in this age group and look out for cutaneous findings that may signal dangerous behavior on social media.

Characterizing the dissemination of misinformation on social media in health emergencies: An empirical study based on COVID-19

The dissemination of misinformation in health emergencies poses serious threats to public health and increases health anxiety. To understand the underlying mechanism of the dissemination of misinformation regarding health emergencies, this study creatively draws on social support theory and text mining. It also explores the roles of different types of misinformation, including health advice and caution misinformation and health help-seeking misinformation, and emotional support in affecting individuals' misinformation dissemination behavior on social media and whether such relationships are contingent on misinformation ambiguity and richness. The theoretical model is tested using 12,101 textual data about COVID-19 collected from Sina Weibo, a leading social media platform in China. The empirical results show that health caution and advice, help seeking misinformation, and emotional support significantly increase the dissemination of misinformation. Furthermore, when the level of ambiguity and richness regarding misinformation is high, the effect of health caution and advice misinformation is strengthened, whereas the effect of health help-seeking misinformation and emotional support is weakened, indicating both dark and bright misinformation ambiguity and richness. This study contributes to the literature on misinformation dissemination behavior on social media during health emergencies and social support theory and provides implications for practice.

Categorising patient concerns using natural language processing techniques

Objectives

Patient feedback is critical to identify and resolve patient safety and experience issues in healthcare systems. However, large volumes of unstructured text data can pose problems for manual (human) analysis. This study reports the results of using a semiautomated, computational topic-modelling approach to analyse a corpus of patient feedback.

Methods

Patient concerns were received by Alberta Health Services between 2011 and 2018 (n=76 163), regarding 806 care facilities in 163 municipalities, including hospitals, clinics, community care centres and retirement homes, in a province of 4.4 million. Their existing framework requires manual labelling of pre-defined categories. We applied an automated latent Dirichlet allocation (LDA)-based topic modelling algorithm to identify the topics present in these concerns, and thereby produce a framework-free categorisation.

Results

The LDA model produced 40 topics which, following manual interpretation by researchers, were reduced to 28 coherent topics. The most frequent topics identified were communication issues causing delays (frequency: 10.58%), community care for elderly patients (8.82%), interactions with nurses (8.80%) and emergency department care (7.52%). Many patient concerns were categorised into multiple topics. Some were more specific versions of categories from the existing framework (eg, communication issues causing delays), while others were novel (eg, smoking in inappropriate settings).

Discussion

LDA-generated topics were more nuanced than the manually labelled categories. For example, LDA found that concerns with community care were related to concerns about nursing for seniors, providing opportunities for insight and action.

Conclusion

Our findings outline the range of concerns patients share in a large health system and demonstrate the usefulness of using LDA to identify categories of patient concerns.

Social Support as a Protective Factor for the Well-Being of Parents of Children with Autism in Saudi Arabia

PURPOSE

Parents of children with autism spectrum disorder (ASD) experience higher levels of stress and impaired life satisfaction as a result of their children's behavior. The well-acknowledged protective role of social support against stress has not been studied in detail with regard to parents of children with ASD in the Kingdom of Saudi Arabia (KSA). Therefore, the purpose of this study is to assess the impact of social support as a mediator and/or a moderator between parental stress and life satisfaction among parents of children with ASD in KSA.

DESIGN AND METHOD

A cross-sectional survey was conducted among centers that care for children with autism in KSA. The survey encompassed four dimensions: demographic data, family stress and coping, parenting life satisfaction, and perceived social support. Multiple linear regression analyses were conducted to assess the moderating and/or mediating effect of social support.

RESULTS

The analysis of 131 parents indicated that perceived family and parental stress was associated with life satisfaction levels, and this relationship was approximately 0.19 points lower when mediated by social support (β = -0.19, 95% CI [-0.34, -0.05], p = .02). Social support moderated the relationship between family stress and life satisfaction, which was significant at low (p = .002) and average levels of stress (p = .017) but not at high levels of stress.

CONCLUSION

Social support is protective for parents of children with ASD.

PRACTICE IMPLICATIONS

Social support, including the use of social media groups, should be considered in supporting stressed parents of children with ASD. Therefore, the protective role of social support should be highlighted to healthcare professionals.

Characterization and Comparison of the Utilization of Facebook Groups Between Public Medical Professionals and Technical Communities to Facilitate Idea Sharing and Crowdsourcing During the COVID-19 Pandemic: Cross-sectional Observational Study

BACKGROUND

Strict social distancing measures owing to the COVID-19 pandemic have led people to rely more heavily on social media, such as Facebook groups, as a means of communication and information sharing. Multiple Facebook groups have been formed by medical professionals, laypeople, and engineering or technical groups to discuss current issues and possible solutions to the current medical crisis.

OBJECTIVE

This study aimed to characterize Facebook groups formed by laypersons, medical professionals, and technical professionals, with specific focus on information dissemination and requests for crowdsourcing.

METHODS

Facebook was queried for user-created groups with the keywords "COVID," "Coronavirus," and "SARS-CoV-2" at a single time point on March 31, 2020. The characteristics of each group were recorded, including language, privacy settings, security requirements to attain membership, and membership type. For each membership type, the group with the greatest number of members was selected, and in each of these groups, the top 100 posts were identified using Facebook's algorithm. Each post was categorized and characterized (evidence-based, crowd-sourced, and whether the poster self-identified). STATA (version 13 SE, Stata Corp) was used for statistical analysis.

RESULTS

Our search yielded 257 COVID-19-related Facebook groups. Majority of the groups (n=229, 89%) were for laypersons, 26 (10%) were for medical professionals, and only 2 (1%) were for technical professionals. The number of members was significantly greater in medical groups (21,215, SD 35,040) than in layperson groups (7623, SD 19,480) (P<.01). Medical groups were significantly more likely to require security checks to attain membership (81% vs 43%; P<.001) and less likely to be public (3 vs 123; P<.001) than layperson groups. Medical groups had the highest user engagement, averaging 502 (SD 633) reactions (P<.01) and 224 (SD 311) comments (P<.01) per post. Medical professionals were more likely to use the Facebook groups for education and information sharing, including academic posts (P<.001), idea sharing (P=.003), resource sharing (P=.02) and professional opinions (P<.001), and requesting for crowdsourcing (P=.003). Layperson groups were more likely to share news (P<.001), humor and motivation (P<.001), and layperson opinions (P<.001). There was no significant difference in the number of evidence-based posts among the groups (P=.10).

CONCLUSIONS

Medical professionals utilize Facebook groups as a forum to facilitate collective intelligence (CI) and are more likely to use Facebook groups for education and information sharing, including academic posts, idea sharing, resource sharing, and professional opinions, which highlights the power of social media to facilitate CI across geographic distances. Layperson groups were more likely to share news, humor, and motivation, which suggests the utilization of Facebook groups to provide comedic relief as a coping mechanism. Further investigations are necessary to study Facebook groups' roles in facilitating CI, crowdsourcing, education, and community-building.

Caregivers' Experience of Caring for a Family Member with Alzheimer's Disease: A Content Analysis of Longitudinal Social Media Communication

Background: The population aging together with an increased incidence of Alzheimer’s disease (AD) should also be accompanied by a growing interest in healthcare research. Therefore, this study examines the nature of the caregiver’s work, its mental and physical demands, experience and questions, and the relationship between the person with AD, the caregiver, and family members. Methods: As social media has become the place where people share family situations, a Facebook private discussion group of caregivers was chosen as the analytical data source. The study documented the daily-life situations of one-hundred dyads based on 2110 posts published during a six-month or longer period. A content analysis classified communication into 35 categories of basic, instrumental, and extended activities of daily livings (ADLs) and newly designed caregiver’s daily issues (CDIs). Results: The frequently discussed topics were related to exhaustion and feelings of “giving up” by caregivers and interpersonal communication and help from family members. The highest support was found for the topics of aging and dying and family events. Conclusion: The communications of caregivers were diverse and rather associated with co-occupational ADLs and CDIs than basic or instrumental ADLs. The support of the group was mainly provided in coping with fundamental life changes.

The Voice of Drug Consumers: Online Textual Review Analysis Using Structural Topic Model

Many web-based pharmaceutical e-commerce platforms allow consumers to post open-ended textual reviews based on their purchase experiences. Understanding the true voice of consumers by analyzing such a large amount of user-generated content is of great significance to pharmaceutical manufacturers and e-commerce websites. The aim of this paper is to automatically extract hidden topics from web-based drug reviews using the structural topic model (STM) to examine consumers’ concerns when they buy drugs online. The STM is a probabilistic extension of Latent Dirichlet Allocation (LDA), which allows the consolidation of document-level covariates. This innovation allows us to capture consumer dissatisfaction along with their dynamics over time. We extract 12 topics, and five of them are negative topics representing consumer dissatisfaction, whose appearances in the negative reviews are substantially higher than those in the positive reviews. We also come to the conclusion that the prevalence of these five negative topics has not decreased over time. Furthermore, our results reveal that the prevalence of price-related topics has decreased significantly in positive reviews, which indicates that low-price strategies are becoming less attractive to customers. To the best of our knowledge, our work is the first study using STM to analyze the unstructured textual data of drug reviews, which enhances the understanding of the aspects of drug consumer concerns and contributes to the research of pharmaceutical e-commerce literature.

Social Media and Health Promotion

With over 3 billion users worldwide, social media has become a staple of daily life for people across the globe [...].

Study on Differences between Patients with Physiological and Psychological Diseases in Online Health Communities: Topic Analysis and Sentiment Analysis

The development of online social platforms has promoted the improvement of online health communities (OHCs). However, OHCs often ignore differences in user discussions caused by the characteristics of diseases. The purpose of this research was to study differences in the topics and emotions of patients with physiological and psychological diseases by mining the text that they posted in OHCs as well as to discuss how to satisfy these differences. The data came from Baidu Post Bar, the world's biggest Chinese forum. We collected 50,230 posts from heart disease, hypertension, depression and obsessive-compulsive bars. Then, we used topic modeling and sentiment analysis techniques on these posts. The results indicate that there are significant differences in the preferences of discussion and emotion between patients with physiological and psychological diseases. First, people with physiological diseases are more likely to discuss treatment of their illness, while people with psychological diseases are more likely to discuss feelings and living conditions. Second, psychological disease patients' posts included more extreme and negative emotions than those of physiological disease patients. These results are helpful for society to provide accurate medical assistance based on disease type to different patients, perfecting the national medical service system.