BackgroundThe rapid spread of Web-based social media in recent years has impacted how patients share health-related information. However, little work has studied the demographics of these users.ObjectiveOur aim was to study the demographics of users who participate in health-related Web-based social outlets to identify possible links to health care disparities.MethodsWe analyze and compare three different types of health-related social outlets: (1) general Web-based social networks, Twitter and Google+, (2) drug review websites, and (3) health Web forums. We focus on the following demographic attributes: age, gender, ethnicity, location, and writing level. We build and evaluate domain-specific classifiers to infer missing data where possible. The estimated demographic statistics are compared against various baselines, such as Internet and social networks usage of the population.ResultsWe found that (1) drug review websites and health Web forums are dominated by female users, (2) the participants of health-related social outlets are generally older with the exception of the 65+ years bracket, (3) blacks are underrepresented in health-related social networks, (4) users in areas with better access to health care participate more in Web-based health-related social outlets, and (5) the writing level of users in health-related social outlets is significantly lower than the reading level of the population.ConclusionsWe identified interesting and actionable disparities in the participation of various demographic groups to various types of health-related social outlets. These disparities are significantly distinct from the disparities in Internet usage or general social outlets participation.

Background Our previous infodemiological study was performed by manually mining health-effect data associated with electronic cigarettes (ECs) from online forums. Manual mining is time consuming and limits the number of posts that can be retrieved. Objective Our goal in this study was to automatically extract and analyze a large number (>41,000) of online forum posts related to the health effects associated with EC use between 2008 and 2015. Methods Data were annotated with medical concepts from the Unified Medical Language System using a modified version of the MetaMap tool. Of over 1.4 million posts, 41,216 were used to analyze symptoms (undiagnosed conditions) and disorders (physician-diagnosed terminology) associated with EC use. For each post, sentiment (positive, negative, and neutral) was also assigned. Results Symptom and disorder data were categorized into 12 organ systems or anatomical regions. Most posts on symptoms and disorders contained negative sentiment, and affected systems were similar across all years. Health effects were reported most often in the neurological, mouth and throat, and respiratory systems. The most frequently reported symptoms and disorders were headache (n=939), coughing (n=852), malaise (n=468), asthma (n=916), dehydration (n=803), and pharyngitis (n=565). In addition, users often reported linked symptoms (eg, coughing and headache). Conclusions Online forums are a valuable repository of data that can be used to identify positive and negative health effects associated with EC use. By automating extraction of online information, we obtained more data than in our prior study, identified new symptoms and disorders associated with EC use, determined which systems are most frequently adversely affected, identified specific symptoms and disorders most commonly reported, and tracked health effects over 7 years.

BackgroundAn increasing number of patients from diverse demographic groups share and search for health-related information on Web-based social media. However, little is known about the content of the posted information with respect to the users’ demographics.ObjectiveThe aims of this study were to analyze the content of Web-based health-related social media based on users’ demographics to identify which health topics are discussed in which social media by which demographic groups and to help guide educational and research activities.MethodsWe analyze 3 different types of health-related social media: (1) general Web-based social networks Twitter and Google+; (2) drug review websites; and (3) health Web forums, with a total of about 6 million users and 20 million posts. We analyzed the content of these posts based on the demographic group of their authors, in terms of sentiment and emotion, top distinctive terms, and top medical concepts.ResultsThe results of this study are: (1) Pregnancy is the dominant topic for female users in drug review websites and health Web forums, whereas for male users, it is cardiac problems, HIV, and back pain, but this is not the case for Twitter; (2) younger users (0-17 years) mainly talk about attention-deficit hyperactivity disorder (ADHD) and depression-related drugs, users aged 35-44 years discuss about multiple sclerosis (MS) drugs, and middle-aged users (45-64 years) talk about alcohol and smoking; (3) users from the Northeast United States talk about physical disorders, whereas users from the West United States talk about mental disorders and addictive behaviors; (4) Users with higher writing level express less anger in their posts.ConclusionWe studied the popular topics and the sentiment based on users' demographics in Web-based health-related social media. Our results provide valuable information, which can help create targeted and effective educational campaigns and guide experts to reach the right users on Web-based social chatter.

Background The increasing volume of health-related social media activity, where users connect, collaborate, and engage, has increased the significance of analyzing how people use health-related social media. Objective The aim of this study was to classify the content (eg, posts that share experiences and seek support) of users who write health-related social media posts and study the effect of user demographics on post content. Methods We analyzed two different types of health-related social media: (1) health-related online forums—WebMD and DailyStrength—and (2) general online social networks—Twitter and Google+. We identified several categories of post content and built classifiers to automatically detect these categories. These classifiers were used to study the distribution of categories for various demographic groups. Results We achieved an accuracy of at least 84% and a balanced accuracy of at least 0.81 for half of the post content categories in our experiments. In addition, 70.04% (4741/6769) of posts by male WebMD users asked for advice, and male users’ WebMD posts were more likely to ask for medical advice than female users’ posts. The majority of posts on DailyStrength shared experiences, regardless of the gender, age group, or location of their authors. Furthermore, health-related posts on Twitter and Google+ were used to share experiences less frequently than posts on WebMD and DailyStrength. Conclusions We studied and analyzed the content of health-related social media posts. Our results can guide health advocates and researchers to better target patient populations based on the application type. Given a research question or an outreach goal, our results can be used to choose the best online forums to answer the question or disseminate a message.

BACKGROUND Our previous infodemiological study was performed by manually mining health-effect data associated with electronic cigarettes (ECs) from online forums. Manual mining is time consuming and limits the number of posts that can be retrieved. OBJECTIVE Our goal in this study was to automatically extract and analyze a large number (>41,000) of online forum posts related to the health effects associated with EC use between 2008 and 2015. METHODS Data were annotated with medical concepts from the Unified Medical Language System using a modified version of the MetaMap tool. Of over 1.4 million posts, 41,216 were used to analyze symptoms (undiagnosed conditions) and disorders (physician-diagnosed terminology) associated with EC use. For each post, sentiment (positive, negative, and neutral) was also assigned. RESULTS Symptom and disorder data were categorized into 12 organ systems or anatomical regions. Most posts on symptoms and disorders contained negative sentiment, and affected systems were similar across all years. Health effects were reported most often in the neurological, mouth and throat, and respiratory systems. The most frequently reported symptoms and disorders were headache (n=939), coughing (n=852), malaise (n=468), asthma (n=916), dehydration (n=803), and pharyngitis (n=565). In addition, users often reported linked symptoms (eg, coughing and headache). CONCLUSIONS Online forums are a valuable repository of data that can be used to identify positive and negative health effects associated with EC use. By automating extraction of online information, we obtained more data than in our prior study, identified new symptoms and disorders associated with EC use, determined which systems are most frequently adversely affected, identified specific symptoms and disorders most commonly reported, and tracked health effects over 7 years.