I. Introduction
There has been a rapid transformation in health technology trends in the recent years. Among various ways of exploring these trends, social media analysis has surfaced as a useful methodology [
1]. With the shift of empowerment of health information to consumers, health consumers are aggressively using social media to share their experiences and collect opinions from others [
2]. Among the various types of social media, Twitter is characterized by its real-time features, strong delivery, publicness, causal ambience, and individuality [
3]. Furthermore, unlike other social media platforms that feature a bidirectional network among users, Twitter features a unidirectional structure, wherein users simply follow and read tweets by other users, companies, and media of their interest [
4]. This structure enhances Twitter's ability to disseminate information.
In a previous study that analyzed Twitter data in 2009 during the spread of the H1N1 virus, only about 5% of the messages contained incorrect information, and Twitter users acquire personal experiences by retweeting information that they have gained indirectly [
5]. In other words, Twitter users share personal experiences and concerns related to health and diseases by tweeting, and the retweeting of these messages by others indicates that their content is interesting and potentially influential. Twitter data contains a writer's opinions or emotions about a topic; therefore, it is possible to analyze the public's mood about a specific topic through opinion mining, through which extreme words are extracted from sentences containing keywords of interest [
6]. Applying opinion mining and sentiment analysis techniques to big online data for the extraction of useful information on any event or topic is gaining more and more interest with the growing number of internet users and recent developments in information and communication technologies (ICT) [
7]. Understanding user profiles, preferences, and barriers can help providers prioritize where to direct efforts when using evidence-based social media in their practice [
8]. Moreover, social media, a communication boon for the public health community has the potential to promote and change many health-related behaviors and issues, particularly in times of crisis [
9].
Therefore, analysis of social media data would be beneficial for understanding potential healthcare consumers because this data is voluntarily created by users, unlike the data produced in controlled environments, such as date obtained through surveys or interviews.
Considering the rapid advances in health technology, investigating traditional standardized data would be a limited approach to trend analysis. In the present study, we analyzed health technology trends and the sentiments of users who have posted content on relevant topics in the past seven years by using Twitter data to examine the public's opinions about health technology and identify their needs.
IV. Discussion
Recent advances in mobile internet and ICT have enhanced connectivity, regardless of time and place, and have thus contributed significantly to various healthcare solutions. Various health problems, such as the increasing number of chronic diseases and the high cost of health services, highlight the need to empower patients and families to practice self-care; hence, the need to provide direct access to health services has emerged over the years [
16]. Recently, mHealth solutions have been found to address these health problems regardless of time and place. For this reason, interests in mHealth have risen; thus, posts about mHealth were found to be the most frequent in our study. Myriad mobile applications have been introduced that promote health and disease self-management. As of 2012, there were about 13,000 health apps for consumers on the Apple AppStore, of which 5.8% were related to mental health, 4.13% to sleep, and 11.44% to stress and relaxation [
17]. A 2013 study reported the existence of 14,000 health apps, of which 558 were for mental health and behavioral disorders, out of which two-thirds were for autism, anxiety, depression, and attention deficit hyperactivity disorder [
18].
Clearly, mHealth has an enormous potential for enhancing healthcare and quality of life. Multiple studies have reported that utilizing mHealth can cut costs and improve patients' clinical outcomes [
1920]. Furthermore, big data obtained from mHealth are expected to offer new insights for research that aims to enhance the quality of various healthcare services.
According to annual trends, posts about telemedicine, privacy, and consumer health informatics peaked in 2013 and 2015. Telemedicine reimbursement is now being provided by several individual states for Medicaid and/or commercial payers. These state-level policy changes are likely to have significant impact on the viability of telemedicine programs and the utilization of services from all payers, and not just on those services and payers who are affected directly by state policy. This is because telemedicine programs are required to serve patients from almost all payers [
21]. In 2013 and 2015, the telemedicine parity legislation was passed or expanded in several states of the United States. This shows that advances in telemedicine were coupled with institutional measures, which led to increasing interest in the matter. The introduction and usage of telehealth in Korea is lagging behind its implementation in other countries, largely due to the lack of policy and adequate legislation [
22]. In addition to continuous exploration of the needs for telemedicine and analysis of its effects through pilot studies, discussions regarding relevant institutional support are also needed.
Sentiment analysis of healthcare suggests the services that consumers prefer [
23]. In this study, most sentimental scores for health technology were positive. These results, like those of previous studies, have proven that Twitter data helps us better understand consumers' positive feelings about health technology and that Twitter is a useful platform for sharing positive opinions on this topic [
24]. However, posts about privacy had negative sentimental scores in 2013 and 2015. This suggests that consumers have concerns regarding privacy as their health information is increasingly being handled digitally. Along with the expansion of the digital world, public attitudes toward privacy are also evolving [
25]. According to one report, 80% of the digital data stored in the United States are pertinent to consumers, and the majority are data related to consumers' lives, such as metadata, medical records, and imaging, as opposed to data created by consumers, such as emails and photographs. In a study that investigated the state of privacy practices for health on social networking sites, the authors pointed out that discussions about specific security measures to protect consumers' personal information are lacking [
27]. The exchange of healthcare-related data containing personal information will be facilitated in the coming years. Therefore, continuous discussions on privacy are needed to ensure that healthcare consumers can utilize various ICT-based services more safely. In 2013, there were also negative scores for health information and medical technology. Considering that the number of postings related to telemedicine, privacy, and consumer health informatics in 2013 was high, the fact that consumer interest was high does not mean that this topic should be evaluated positively. It is necessary to review the implications of negative emotions for health technology through future research.
Examining social media users' responses to new health technology can be useful to understand the trends in rapidly evolving fields. Recent research has mainly focused on the ‘health’ keyword itself, which is rather broad. However, this study went one step forward by classifying health technology into subcategories, such as health technology, wearable technology, biotechnology, mobile health, and medical technology. Moreover, health information was classified into the four subcategories of health information, privacy, clinical informatics, and consumer health informatics. By classifying the word above, the significance of this study is that it visualized the trends of health information technology in social media. The impact of technology in the healthcare field has been investigated in many studies by healthcare providers. Also, most of them have focused on the expert's point of view for providing healthcare services to the patients. However, we were able to examine the interests and sentiments of potential healthcare consumers regarding health information technology by analyzing social media data in this study. It would be better to understand the demands for healthcare technology from the consumer's perspective and apply it to new system development. Nevertheless, this study had a few limitations. First, there were more male Twitter users than female, with the majority of them being young adults and belonging to a single country. Therefore, our findings should be interpreted with caution. Furthermore, we only used subcategory titles and included the contents of the posts in the analysis. In subsequent studies, subcategory keywords should be used to observe the number of retweets (copying and reposting of tweets or replying to tweets), identify important users who post a significant number of tweets on the topic, and conduct analysis based on countries and regions so as to provide more prompt and accurate insights into trends related to healthcare personnel.