Background China is at the forefront of global efforts to develop COVID-19 vaccines and has five fast-tracked candidates final-stage, large-scale human clinical trials testing phase. Vaccine-promoting policymaking for public engagement a prerequisite social mobilization. However, making an informed judicious choice dilemma Chinese government in vaccine promotion context. Objective In this study, opinions were analyzed via dialogues on media, based which netizens’ views vaccination...

The outbreak of a novel coronavirus (COVID-19) generated an public opinions in the Chinese Sina-microblog. To help designing effective communication strategies during major health emergency, we propose multiple-information susceptible-discussing-immune (M-SDI) model order to understand patterns key information propagation on social networks. We develop M-SDI model, based discussion quantity and take into account behavior that users may re-enter another related topic or Weibo after discussing...

Sentiment lexicon, which provides sentiment information for words, plays an important role in analysis task. Currently, most of lexicons have only one polarity each word and ignore sentimental ambiguity. In this paper, we propose to construct the lexicon based on context-dependent part-of-speech (POS) chunks, namely CP-chunks, aims at solving ambiguity lexical sentiments. Given that POS context has impact intensity, take CP-chunks as unit do calculation. Our method is evaluated through...

Abstract In the context of COVID-19 pandemic, global vaccine campaigns are a mass vaccination intervention conducted through routine service provision for individuals who have reached specified age. However, obtaining high uptake rate to reach herd immunity may be undermined by various social motivations. To scrutinize practical and dynamic strategies successful campaign, we map out determinants that exacerbate hesitancy leveraging capacity rich metadata from Twitter. Here, uncover...

Backgroud Effective communication of accurate information through social media constitutes an important component public health interventions in modern time, when traditional approaches such as contact tracing, quarantine and isolation are among the few options for containing disease spread population. The success control COVID-19 outbreak started from Wuhan, capital city Hubei Province China relies heavily on resilience residents to follow which induce substantial interruption...

The warehouse model, based on differential equations, has been widely employed in the field of network information propagation for an extended period. Numerous studies have revolved around construction, fitting and simulation these models. However, there not a universal efficient method applicable to all models realm propagation, mainly due often challenging nature solving equations practical scenarios. In this article, we introduce deep learning-based framework simulating dynamics. This is...

Everyone has a different level of interest in trending topic posted on social media, which may affect user's behaviour. In order to find out the way it affects process information transmission, we construct an intensity-based susceptible-forwarding-immuneI−SFI propagation dynamic model and two parameters birth rateA death rateμ are introduced represent users who newly join group disseminated leave this population. And give rates people with various levels interest, helps us determine...

Abstract The boom in the field of movies and TV programs, which is a kind information overload, may lead to poor user experience are detrimental healthy development industry, hence personalized program recommendation crucial. Since names, labels, synopsis highly condensed languages, enable better semantic representations for recommendations enrich completeness requirements data resources, we propose an enhanced graph with heterogeneous auxiliary (EGR-HA), focusing on knowledge...

Background In a fast-evolving public health crisis such as the COVID-19 pandemic, multiple pieces of relevant information can be posted sequentially on social media platform. The interval between subsequent posting times may have different impact transmission and cross-propagation old new that results in peak value final size forwarding users information, depending content correlation whether is during outbreak or quasi–steady-state phase information. Objective This study aims to help...

In the existing researches, mining and prediction of core group in communication network are difficult to be correlated. addition, focus for monitoring events cannot concentrated. order solve these problems, this paper researches method based on Walk Trap ARIMA algorithm. It proposes an optimized combining degree centrality algorithm, then puts forward flagged line graph connect results subsequent forecast. way, coverage groups can effectively identified so as facilitate monitoring. The...

When the weight of each attribute is determined in multiple decision making problems, calculated by method subjective values or objective solely will cause problem that coefficient not reasonable.So paper puts forward weightingmethod which based on maximizing deviations and normalized constraint condition.The integrates weighting information.On one hand, deviation between vector various makes maximum its total deviation.On other evaluated object integrated value value.Thus we establish a...

With the rise of social networks, various types information have emerged in vision field a complex manner, making it crucial to analyze propagation patters online public opinion effectively guide dissemination. To elucidate dynamics dissemination, this paper proposes directed network based on self-organized dissemination scenario. This model takes into account influence networks formed by users spontaneously and distinguishes population in- out-degree user nodes network. assess model's...