Font Size: a A A

Research On The Features Of Senior Online Health Communities Users From The Perspective Of Knowledge Service

Posted on:2021-07-21Degree:MasterType:Thesis
Country:ChinaCandidate:Y X QianFull Text:PDF
GTID:2544306290498834Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
The population aging trend known as the "Silver Wave" is a significant challenge China is facing.The rapid spread of the Internet and the rapid development of information technology are other aspects of the contemporary society.Providing health knowledge services for the elderly is an important measure to actively respond to the problem of aging,and the study of user features is the basis for developing health knowledge services for the elderly.This article selects two of the most representative senior online communities,yinling.com and keai99.com,and comprehensively utilizes various user data from health-related sectors in the online community to conduct research.In the first chapter,from the two social backgrounds of aging society and information society,the significance of providing health knowledge services for the elderly is elaborated and then combined with the current research background of health knowledge services,with the research questions and research goals of this article proposed.The second chapter focuses on the literature review of this research perspective—knowledge service and this research scenario—the online health community.Based on sorting out the current research situation and the lack of research in these two aspects,this paper will change from the perspective of information services to knowledge services,and propose the significance and value of health knowledge service from three aspects of user health knowledge needs,health knowledge communication behavior,and health knowledge feedback,and further clarify the research content of this article.In the third chapter,research is performed on the features of the health knowledge needs of senior users.Firstly,a health knowledge classification system is constructed based on the results of word frequency analysis.The BERT model is used to train the classifier from knowledge topics and medical types on health knowledge posts posted by users.From the quantitative composition of different types of health knowledge,and the differences in user attention,the user’s health knowledge needs are analyzed.Besides,the user’s health knowledge needs are analyzed in terms of medical types and the dynamic changes of user health knowledge needs.The health knowledge needs of senior users are mainly concentrated on the physiological and physical health levels,where there is a certain preference for the type of medicine,and it is found that the amount of various types of health knowledge is inconsistent with the level of user attention.In the fourth chapter,the research on the features of health knowledge communication behaviors of senior users mainly uses descriptive statistical analysis and correlation analysis through indicators such as the number of users participating,the number of posts posted by users,the number of replies,and the number of page views,to reveal the distribution and trend of user activity.Then we perform social network analysis based on the user’s reply relationship network and analyze user cohesion through network attributes.Health knowledge sharing depends on a few users,and there are a large number of silent users.The online community lacks effective incentives for user knowledge communication.In the fifth chapter,the research on the features of senior users’ feedback of health knowledge mainly focuses on the emotional and semantic features of user replies.A sentiment analysis method based on sentiment dictionaries explores the sentiment features of user replies texts,analyzes the differences in the sentiment distribution of users in the two online communities,and the user’s sentiment differences on different types of health knowledge.The study of semantic features is mainly to use the replies text to draw a word cloud map based on word frequency and to summarize and analyze the main functions of the reply text and the language features of the senior users.Most senior users have a positive attitude towards health knowledge.The user’s feedback content has three main functions of attitude expression,daily communication and health issues discussion,while positive attitude expression and daily communication are majority.In the sixth chapter of the discussion on the senior health knowledge service model,based on the previous research on the three features of senior users,the main challenge faced by the current senior health knowledge service is the apparent imbalances and inconsistencies among their strong desire for health knowledge,the current unfavorable external Internet environment,and the relatively insufficient capabilities of themselves.In response to these challenges,the framework of the senior health knowledge service model is proposed.From the aspects of health knowledge base construction and management,form of health knowledge service,and empowerment of elderly users,the key points of the content and form of the senior health knowledge service are discussed,and gave suggestions to the service providers and practitioners of the smart senior care platform to better provide health knowledge services for senior users.From the perspective of knowledge service,this article presents and reveals the features of the health knowledge needs,health knowledge communication behavior,and health knowledge feedback of the senior online health community users as a whole.On the one hand,it makes up for the lack of existing research on senior online users and insufficient attention to knowledge services.On the other hand,this article provides a practical basis and reference for the content and form of developing senior health knowledge services,intending to play a decisive role in dealing with aging problems through smart senior care and other measures in the future.
Keywords/Search Tags:online health community, senior Internet users, user feature, knowledge services, text mining
PDF Full Text Request
Related items