The research process mainly included five steps: (1) collecting topics related to the COVID-19 epidemic on the Sina Microblog hot search list; (2) segmenting the collected text into words; (3) describing the Sina Microblog search trend around the COVID-19 epidemic; (4) evaluating public opinion through word frequency and sentiment analysis; and (5) constructing a social network of public opinion through the subject analysis of the content. Each step is described in detail below.

We obtained information on COVID-19 in mainland China from the National Health Committee of the People’s Republic of China [46]. The Wuhan Municipal Health Committee first reported viral pneumonia of unknown causes on December 31, 2019 [47]. This study collected topics on the Sina Microblog hot search list from December 31, 2019, to February 20, 2020, using Weibo Search Rank [48] from ENLIGHTENT [49], and selected topics and their search volume related to the COVID-19 epidemic. A total of 4056 topics related to the COVID-19 epidemic were on the hot search list, and 3234 remained after excluding duplicate topics. This group was used as the data basis for further processing, analysis, and discussion.

The topics related to the COVID-19 epidemic on the Sina Microblog hot search list from December 31, 2019, to February 20, 2020, were summarized and classified daily in chronological order. We used the Chinese word segmentation function in ROST Content Mining System Version 6.0 (ROST CM6.0) to segment the content of hot search topics on Sina Microblog into words [50]. After word segmentation, the text was processed by merging synonyms and deleting nonsense words to provide a basis for subsequent research.

Figure 1 lists the number of COVID-19 epidemic-related topics and the cumulative search volume on the Sina Microblog hot search list from December 31, 2019, to February 20, 2020. The Pearson correlation analysis shows that the number of topics related to the COVID-19 epidemic is positively correlated with the cumulative search volume of the topic per day (r=0.767, P<.001). In other words, the more topics that are listed, the greater the cumulative search volume related to the COVID-19 epidemic per day. We can see that the public’s attention to the COVID-19 epidemic on Sina Microblog can be divided into three stages. Stage A (December 31, 2019, to January 18, 2020) has low and unstable public attention, which represents the incubation period. Stage B (January 19-26, 2020) has a concentrated increase in public attention, which represents the epidemic period. Stage C (January 27 to February 20, 2020) demonstrates continued public attention to the epidemic, representing a widespread period.

The top 15 keywords and their frequencies for the three stages of the public’s attention to the COVID-19 epidemic are shown in Table 1. “Wuhan,” “case,” and “pneumonia” always appeared in the three periods as hot keywords, and the remaining keywords in the different periods were slightly different. In stage A, “unknown cause” and “novel coronavirus” were the main keywords, indicating that in the initial stage of the epidemic, viral pneumonia had just been discovered, and the cause was unknown. After the pathogen was initially identified as a novel coronavirus, the public began to search for information on the novel coronavirus to learn relevant knowledge. Compared with stage A, stage B had new keywords such as “new,” “mask,” “first case,” and “first-level response.” The reason for this is that the COVID-19 epidemic had spread across the country during this stage. The first cases had appeared successively throughout the country, and the number of confirmed cases was increasing. The outbreak of COVID-19 made the people and the government aware of the importance of prevention. People began to buy masks, and governments at all levels initiated first-level responses to major public health emergencies. Compared with the previous two stages, the main keywords appearing in stage C were “discharged,” “national,” “materials,” and “Huoshenshan Hospital.” At this stage, the public’s attention had shifted to material donation and medical service assistance in the key epidemic areas in Wuhan. Moreover, the epidemic had spread throughout the country, and the public was more concerned about the rehabilitation of patients.

After segmentation, we imported the Sina Microblog hot topic text related to the COVID-19 epidemic into the ROST CM6.0 sentiment analysis tool and obtained the sentiment and proportion of the three stages of public attention given to the topics related to the COVID-19 epidemic (Figure 2). Emotions were classified as positive, negative, and neutral emotions. Based on this, positive and negative emotions were subdivided into three categories: general, moderate, and high. Neutral emotions were not subdivided. We found that the sentiment of the hot topics of the COVID-19 epidemic on Sina Microblog in stage A tended to be negative, accounting for 58% (n=14/24), of which high and moderate negative emotions accounted for 13% (n=3) and 17% (n=4), respectively, and positive emotions accounted for the lowest proportion at 8% (n=2). In stage B, the majority of the hot search topics were neutral; however, 27.2% (n=174/639) of the hot search topics showed negative emotions, with 0.3% (n=2) being highly negative and 3.6% (n=23) being moderately negative, while positive emotions accounted for 13.3% (n=85). In stage C, 18.01% (n=470/2610) of the hot search topics showed positive emotions, of which moderate positive emotions accounted for 2.26% (n=59) and highly positive emotions accounted for 0.31% (n=8); in addition, 28.24% (n=737) of the hot search topics showed negative emotions. Based on the comprehensive analysis of the three-stage emotional tendencies, the public’s negative emotions toward the COVID-19 epidemic were weakened as a whole, and their positive emotions were generally enhanced.

Figure 3 shows the trend for the proportion of the daily emotional tendencies of the hot search topics related to the COVID-19 epidemic from December 31, 2019, to February 20, 2020. We can see that the three kinds of emotions are relatively unstable before January 9, 2020. From January 9-20, 2020, negative emotions accounted for the largest proportion, followed by neutral emotions, and positive emotions accounted for the smallest proportion.

Compared with the emotions prior to January 20, 2020, the positive emotions of the hot search topics related to the COVID-19 epidemic after January 20, 2020, were generally on the rise; the negative emotions declined on the whole, and the emotions tended to be stable, as seen in Figure 3. This outcome shows that as the COVID-19 epidemic began to spread throughout the country after January 20, 2020, the public eased their concerns and fears caused by their uncertainty toward and ignorance of the epidemic, and responded to the epidemic with a more objective attitude.

To explore the themes reflected by the related topics of the COVID-19 epidemic on the Sina Microblog hot search list, this study used VOSviewer to generate clusters and co-occurrence networks of topic keywords. The results are shown in Figure 4. In the figure, the larger the size of the nodes and the font, the greater the weight of the keyword is, and it is closer to the core position. The connection between the nodes indicates that the keywords on the two nodes have appeared together. The thicker the connection is, the higher the frequency of co-occurrence and the closer the connection is between the nodes. Nodes with the same color belong to the same cluster.

According to the network visualization graph constructed in Figure 4, we can see that the keyword “COVID-19” is at the core node position, and the two nodes “Wuhan” and “add” are next. The core topic of public concern about the COVID-19 epidemic was COVID-19 itself, and the public was extremely concerned about the status of the epidemic in Wuhan and the new cases. We can divide the high-frequency keywords of topics into five clusters.

Cluster 1 (red cluster) involved discussion related to new cases, the outbreak of COVID-19 across the country, and the impact of the epidemic on the resumption of school and work. Examples of keywords included “case,” “newly increased,” “appear,” “Hubei Province,” and “Beijing” (Figure 5).

Cluster 2 (green cluster) involved searches for news reports on the frontline of the epidemic and related measures for prevention and control. Examples of keywords included “Wuhan,” “front-line,” “inpatient,” “quarantine,” and “living at home” (Figure 6).

Cluster 3 (blue cluster) involved searches for interpretations of the epidemic situation and prevention and control, and the knowledge of experts and relevant health departments, as well as the discussion on the source of the infection. The keywords in this cluster included “academician,” “WHO,” “face mask,” “epidemic prevention,” “symptom,” “virus,” and “SARS-CoV-2” (Figure 7).

Cluster 4 (yellow cluster) included searches for frontline medical services such as frontline hospital construction and medical team support. Examples of keywords in this cluster included “patient,” “hospital,” “Leishenshan,” “Huoshenshan,” and “first batch” (Figure 8).

Cluster 5 (purple cluster) included searches for the worldwide spread of the disease and searching online for fellow passengers with confirmed cases. Examples of keywords in this cluster included “passenger,” “carriage,” “cruise,” “suspend,” “infection,” and “Japan” (Figure 9).

In recent years, as people increasingly seek health information online, social media has played an increasingly important role in public health emergencies [29,35]. However, there have been no relevant studies that have incorporated social media analysis into the public response to the COVID-19 epidemic. We used the Sina Microblog hot search list to analyze the public’s attention toward the COVID-19 epidemic from December 31, 2019, to February 20, 2020, which was 52 days after the first disclosure of COVID-19 by the Chinese health department. There were four main findings from this study. First, we analyzed the changing trend of public attention given to the COVID-19 epidemic, which can be divided into three stages. Second, the hot topic keywords of the public’s attention at each stage were slightly different. Third, the public’s emotional tendency toward the hot search topics related to the COVID-19 epidemic changed from negative to neutral across the study period. As a whole, negative emotions weakened, and positive emotions increased. Fourth, we divided the topics of public concern about the COVID-19 epidemic into five categories through social semantic network analysis. This study analyzes the public’s response and attention given to the COVID-19 epidemic, which will help public health professionals monitor public response, identify public needs as early as possible, make timely public health prevention and control measures, and disseminate knowledge to citizens in a targeted manner to better respond to the current COVID-19 epidemic.

From December 31, 2019, to February 20, 2020, the public attention given to the COVID-19 epidemic on Sina Microblog can be divided into three stages. In the beginning, there was little public attention paid to the epidemic, and then the concentration of attention increased. Next, the public attention given to the epidemic generally declined, but people continued to pay attention. In the first stage (December 31, 2019, to January 18, 2020), the Chinese public paid less attention, as COVID-19 was only reported in Wuhan, China. On January 19, 2020, suspected cases appeared in Shanghai and Shenzhen, and body temperatures began to be measured at the Wuhan Airport and Railway Station. People began to notice the severity of the epidemic, and the level of attention paid to the COVID-19 epidemic began to increase until January 26, 2020. We can see that when the epidemic began to spread across the country, the public responded quickly to news about the COVID-19 outbreak on Sina Microblog [39]. This is because COVID-19 is a new infectious disease, which means that no effective treatment has been found and no corresponding vaccine has been developed. When the outbreak began, the public was eager to search for relevant knowledge and information online to meet their own protection needs [27,30]. In the third stage (January 27 to February 20, 2020), although the number of cases of COVID-19 were still increasing, the number of Sina Microblog topics and their search volume were decreasing. The reason for this may be because the epidemic information was relatively saturated, and it was difficult for people to acquire more new knowledge through a Sina Microblog search [27]. It may also be that people were no longer paying close attention to the epidemic dynamic to gain a sense of security as time went on, and the public’s consciousness tends to be rational [52].

The keywords for the three different stages of the public’s attention to the COVID-19 epidemic were slightly different. From the hot search keywords of each stage, we found that the public did not know much about the virus and its causes in the first stage. The main keywords of the search to seek relevant knowledge were “unknown cause” and “novel coronavirus.” During the second stage, the epidemic began to spread throughout the country, the first cases were reported in different areas successively, and the number of confirmed cases continued to increase, thereby making the public and government aware of the importance of prevention. During the third stage, the epidemic spread widely throughout the country; Wuhan was the most seriously affected area, and the city was locked down. The public’s attention was mainly shifted to material donation and medical assistance in Wuhan. Compared with qualitative research, it is more accurate to obtain the hot spots of public attention through keyword frequency analysis, as this process has a higher accuracy and more credibility in the research of hot spots and their development trends [40]. Based on our high-frequency keyword analysis of the Sina Microblog topics related to the COVID-19 epidemic, we can obtain information about the concerns and opinions of Sina Microblog users at different stages [53]. Studies have found that people’s interest in infectious diseases on social media was linked to the latest news and major events. Studies have also shown that people will pay attention to and search for disease-related words as the spread of infectious diseases change [30].

According to the sentiment tendencies of the hot search topics related to the COVID-19 epidemic on Sina Microblog, the first stage of emotion was negative, and the second and third stages were neutral. On the whole, negative emotions weakened, and positive emotions increased. Previous studies have pointed out that there is also an important relationship between emotions and content on social media [54]. The content analysis of social networks has identified people’s attitudes or reactions to specific health hazard events [30,39]. In the first stage, there was less public attention given to the Sina Microblog hot search list. Most of the topics related to the COVID-19 epidemic were about the notification of pneumonia and the virus, and the emotions tended to be negative. At that time, the public had a strong demand for information on public health emergencies such as infectious diseases. When the information demand could not be fully satisfied, the users’ emotions were negative [40]. As the epidemic progressed to the second and third stages, the public sentiment tended to be neutral because increasingly more news was being reported at this stage, and objective events became the mainstream information on the Sina Microblog hot search list. The public reduced their previous levels of worries and fears about the epidemic; their negative feelings weakened, and their positive emotions increased. More hot search topics mentioned information about prevention or protection, which is conducive to public health communication and promotion.

We divided the COVID-19 topics with the highest levels of public concern into five categories: the situation of new cases of COVID-19 and its impact, frontline reporting of the epidemic and the measures of prevention and control, expert interpretation and discussion on the source of infection, medical services on the frontline of the epidemic, and focus on the worldwide epidemic and looking for suspected cases. From the search of the subject content, we can see that during the outbreak of the novel coronavirus, the public, the news media, and the health department all actively used Sina Microblog as a platform for disseminating information related to COVID-19 [29], indicating that Sina Microblog is a communication channel for both individuals and organizations to publicize COVID-19 symptoms, preventive measures, and related policies [37]. In addition, as a real time and extensive online platform, Sina Microblog provides a channel for information dissemination. For example, in this emergency outbreak, the public has made good use of the platform to find fellow passengers with confirmed cases, thereby playing an important role in preventing and controlling the disease transmission.

There are some limitations to this study. First, our study was limited to the period 52 days after COVID-19 was first disclosed by the Chinese health department. Thus, the situation after February 20, 2020, was not included in this study. Second, we only used Sina Microblog as the social media platform in this study, the data source for this study is relatively narrow. Considering that China is seriously aging and that the majority of internet users are young people, the age of Sina Microblog users is mainly concentrated in those 18-41 years [42], which cannot represent the population of all ages in China. Therefore, selection bias is inevitable in this study. On the other hand, the study excludes other popular social media data sources such as WeChat and ByteDance and is limited to the publicly available data on the Sina Microblog hot search list. Moreover, due to the lack of detailed information about the users who contributed to the search volume of the Sina Microblog hot search list, we could not describe the social demographic information of the Sina Microblog users, and we failed to obtain the geospatial distribution of Sina Microblog active users. Thus, we could not calculate the average attention of the public in different regions of China.

Social media has played a vital role during the spread of the COVID-19 epidemic and has become the main way for the public to obtain epidemic information. However, the excessive amount of information about the novel coronavirus (some right, some wrong) on social media may make it difficult for people to find reliable sources and guidance when needed, and may even be harmful to people’s health, leading to the outbreak of an infodemic [55]. Therefore, misinformation can be easily propagated and spread on social media. Apart from traditional “top-down” public health communication, provider-managed communication platforms such as WebMD (America), AskDr (Singapore), and HaoDF (China) can be used as an additional countermeasure available to develop a ground-up response to this issue. HaoDF [56], one of the largest doctor-patient communication platforms in China, launched an online free consultation service for COVID-19 during this epidemic. Doctors answered questions online for free 24 hours a day to help the public make a preliminary judgment about the disease and avoid blind medical treatment caused by panic. In addition, HaoDF summarized the common questions and answers of COVID-19 to let the public know more about the epidemic. These are the forms of responses, as potential solutions to avoid an infodemic, that governments can engage with, researchers can study, and innovators can develop in the future.

Our study found that social media platforms such as Sina Microblog can be used to measure public attention given to public health emergencies. Our study shows that a large amount of information about the COVID-19 epidemic was disseminated and received widespread public attention on Sina Microblog during the novel coronavirus epidemic. We have learned about the hotspots of public concern regarding the COVID-19 epidemic on Sina Microblog. These findings can help the government and health departments better communicate with the public about public health and then translate public health needs into practice to create targeted measures to prevent and control the spread of COVID-19.