Microblogging

Social media is defined as "a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, that allow the creation and exchange of user-generated content". Social media can be used in medical education to enhance knowledge sharing among peer groups and the public in general. The internet revolutionized learning by allowing easier dissemination of knowledge that did not depend on printing and physical distribution of books, journals, or magazines. According to a report from 2018, 95% of students have access to smartphones and 45% are online at any given time...

Objective: In December 2022, the Chinese government announced the further optimization of the implementation of the prevention and control measures of COVID-19. We aimed to assess internet-using public expression and sentiment toward COVID-19 in the relaxation of control measures in China. Methods: We used a user-simulation-like web crawler to collect raw data from Sina-Weibo and then processed the raw data, including the removal of punctuation, stop words, and text segmentation. After performing the above processes, we analyzed the data in two aspects...

Existing sentiment analysis research on Chinese government affairs microblogs primarily focuses on the task of sentiment classification on microblogs. There has been a lack of investigation into the correlation of each government affairs microblog with the sentiment values of the corresponding comments below it. This study constructs a large-scale government affairs microblog dataset and explore the correlation of each microblog with the sentiment values of the corresponding comments below it. We proposed a new framework that includes data collection, sentiment analysis and sentiment prediction model training...

Currently, sentiment analysis is a research hotspot in many fields such as computer science and statistical science. Topic discovery of the literature in the field of text sentiment analysis aims to provide scholars with a quick and effective understanding of its research trends. In this paper, we propose a new model for the topic discovery analysis of literature. Firstly, the FastText model is applied to calculate the word vector of literature keywords, based on which cosine similarity is applied to calculate keyword similarity, to carry out the merging of synonymous keywords...

Identifying and analyzing the public's opinion of focal events during a major epidemic can help the government grasp the vicissitudes of network public opinion in a timely manner and provide the appropriate responses. Taking the COVID-19 epidemic as an example, this study begins by using Python-selenium to capture the original text and comment data related to COVID-19 from Sina Microblog's CCTV News from Jan. 19, 2020, to Feb. 20, 2020. The study subsequently uses a manual interpretation method to classify the Weibo content and analyzes the shifting focus phenomena of network public opinion based on the moving average method...

During the recent Coronavirus disease 2019 (COVID-19) outbreak, the microblogging service Twitter has been widely used to share opinions and reactions to events. Italy was one of the first European countries to be severely affected by the outbreak and to establish lockdown and stay-at-home orders, potentially leading to country reputation damage. We resort to sentiment analysis to investigate changes in opinions about Italy reported on Twitter before and after the COVID-19 outbreak. Using different lexicons-based methods, we find a breakpoint corresponding to the date of the first established case of COVID-19 in Italy that causes a relevant change in sentiment scores used as a proxy of the country's reputation...

Issues with sentiment analysis in social media include neglecting the long-distance semantic link of emotional features, failing to capture the feature words with emotional hue effectively, and depending excessively on manual annotation. This research provides a user emotion recognition model to achieve the emotional analysis of microblog public opinion events. Three types of inspiring text, "joy," "anger," and "sadness," are obtained by the data collecting and data preprocessing of micro-blog public opinion event comment text...

Sentiments are the key factors that lead to influence our behavior. Sentiment analysis is a technique that analyzes people's behaviors, attitudes, and emotions toward a service, product, topic, or event. Since 2020, no country has remained untouched by COVID-19, and the governing bodies of most countries have been applying several anti-pandemic countermeasures to combat it. In this regard, it becomes tremendously important to analyze people's sentiments when tackling infectious diseases similar to COVID-19...

The COVID-19 pandemic has introduced new norms, such as social distancing, face masks, quarantine, lockdowns, travel restrictions, work/study from home, and business closures, to name a few. The pandemic's seriousness has made people vocal on social media, especially on microblogs such as Twitter. Since the early days of the outbreak, researchers have been collecting and sharing large-scale datasets of COVID-19 tweets. However, the existing datasets carry issues related to proportion and redundancy . We report that more than 500 million tweet identifiers point to deleted or protected tweets...

Microblogging sites are important vehicles for the users to obtain information and shape public opinion thus they are arenas of continuous competition for popularity. Most popular topics are usually indicated on ranking lists. In this study, we investigate the public attention dynamics through the Hot Search List (HSL) of the Chinese microblog Sina Weibo, where trending hashtags are ranked based on a multi-dimensional search volume index. We characterize the rank dynamics by the time spent by hashtags on the list, the time of the day they appear there, the rank diversity, and by the ranking trajectories...

BACKGROUND: Ensuring that students transition smoothly into the identity of a doctor is a perpetual challenge for medical curricula. Developing professional identity, according to cultural-historical activity theory, requires negotiation of dialectic tensions between individual agency and the structuring influence of institutions. We posed the research question: How do medical interns, other clinicians and institutions dialogically construct their interacting identities? METHODS: Our qualitative methodology was rooted in dialogism, Bakhtin's cultural-historical theory that accounts for how language mediates learning and identity...

On social networking sites, people can express themselves in a variety of ways such as creating personalized profiles, commenting on some topics, sharing their experiences and thoughts. Among these technology-enabled features, retweeting other-sourced tweet is a powerful way for users to present themselves. We examine users' retweeting behavior from the perspective of online identity and self-presentation. The empirical results based on a panel dataset crawled from Twitter reveal that, people are prone to retweet topics they are interested in and familiar with, in order to convey a consistent and clear online identity...

More and more individuals are paying attention to the research on the emotional information found in micro-blog comments. TEXTCNN is growing rapidly in the short text space. However, because the training model of TEXTCNN model itself is not very extensible and interpretable, it is difficult to quantify and evaluate the relative importance of features and themselves. At the same time, word embedding can't solve the problem of polysemy at one time. This research suggests a microblog sentiment analysis method based on TEXTCNN and Bayes that addresses this flaw...

During public policy information diffusion, policy interpretation on government microblogs and public attention interact, but there are certain differences. We construct a research framework for the heterogeneous diffusion of public policy information on government microblogs. An empirical study is conducted based on the Network Agenda Setting (NAS) model. First, a combination of topic mining and content analysis is used to identify the issues discussed by government microblogs and citizens. Then, we use the importance of nodes in Degree Structure (DS) and Flow Structure (FS) entropy to measure their attention to different issues...

A systematic study of public participation (Pub) in environmental pollution control can facilitate collaborative governance based on multiple factors, and promote the modernization of national governance. Based on the data of 30 Chinese provinces from 2011 to 2020, this study empirically analyzed the mechanism of Pub in environmental pollution governance. Based on multiple channels, a dynamic spatial panel Durbin model and an intermediary effect model were constructed. The main results are as follows: (1) Pub based on environmental letters and visits have no significant impact on local pollution reduction, while the Baidu search index of environmental pollution has the greatest effect on emission reduction, followed by environmental protection strategies based on the National People's Congress (NPC) and microblogging...

(1) Background: The COVID-19 epidemic is still global and no specific drug has been developed for COVID-19. Vaccination can both prevent infection and limit the spread of the epidemic. Eliminating hesitation to the COVID-19 vaccine and achieving early herd immunity is a common goal for all countries. However, efforts in this area have not been significant and there is still a long way to go to eliminate vaccine hesitancy. (2) Objective: This study aimed to uncover differences in the characteristics and sentiments of COVID-19 vaccine hesitators on Chinese social-media platforms and to achieve a classification of vaccine-hesitant groups...

INTRODUCTION: The dramatic reduction of clinical and research activities within medical and surgical departments during COVID-19, coupled with the inability of medical students to engage in research, away rotations and academic meetings, have all posed important implications on residency match. METHODS: Using Twitter application programming interface available data, 83,000 program-specific and 28,500 candidate-specific tweets were extracted for the analysis. Applicants to urology residency were identified as matched vs unmatched based on 3-level identification and verification...

Scientists increasingly use Twitter for communication about science. The microblogging service has been heralded for its potential to foster public engagement with science; thus, measuring how engaging, that is dialogue-oriented, tweet content is, has become a relevant research object. Tweet content designed in an engaging, dialogue-oriented way is also supposed to link to user interaction (e.g. liking, retweeting). The present study analyzed content-related and functional indicators of engagement in scientists' tweet content, applying content analysis to original tweets ( n  = 2884) of 212 communication scholars...

OBJECTIVES: This study aimed to investigate the linguistic markers of an interest in mindfulness. Specifically, it examined whether individuals who follow mindfulness experts on Twitter use different language in their tweets compared to a random sample of Twitter users. This is a first step which may complement commonly used self-report measures of mindfulness with quantifiable behavioural metrics. METHOD: A linguistic analysis examined the association between an interest in mindfulness and linguistic markers in 1...

Online social media networks are an integral part of modern life. Microblogging sites such as Twitter have hundreds of millions of active users globally and have been enthusiastically adopted by many in the medical profession. For advancing a relatively neglected field such as fungal infection, this can be especially advantageous. Education, research networking, case discussions and public and patient engagement can all be greatly enhanced through the use of social media networks. This review highlights the ways in which this can work successfully in the case of aspergillosis and fungal infection in general, as well as highlighting the dangers and pitfalls of social media medicine...