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Research On The Impact Of Audiences’ Deep Reading Behavior In The Era Of Intellectual Media

Posted on:2024-06-17Degree:MasterType:Thesis
Country:ChinaCandidate:S Y GuoFull Text:PDF
GTID:2558307079462934Subject:Journalism and Communication
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Since 2014,"national reading campaign" has been written into the government work report for ten consecutive times.The report to the 18 th National Congress of the Communist Party of China first proposed "to carry out reading activities for all people",and the report to the 20 th National Congress of the Communist Party of China proposed "to deepen reading activities for all people".The importance of national reading campaign is evident from the successive appearances of "national reading campaign" in the government work reports,and from "carry out" to "deepen" in the reports of the Party Congress.In the current era of intelligent media,mobile internet,artificial intelligence,big data,cloud computing and other intelligent technologies are deeply integrated with other industries.The digital development trend of national reading campaign is becoming increasingly prominent.The use of intelligent technology to cultivate national reading habits and promote reading has become an important path to open up a new realm of national reading campaign.However,the graphic,fragmented and entertaining nature of reading content has led to the phenomenon of shallow reading among the nation,which has affected the development of quality national reading campaign.Therefore,national reading campaign can only be truly achieved if the nation develops a deep reading habit.This thesis looks at the factors influencing audiences’ deep reading behaviour in the era of intelligent media,and explores how intelligent technology can be used to promote the development of national habits of deep reading behaviour,in order to promote high-quality development of national reading campaign.Starting from the actual background,this thesis first explains the performance and characteristics of Chinese national reading behaviour in the era of intelligent media.And based on information processing theory,the various aspects of the whole process of deep reading are sorted out.Then,18 users using mobile reading devices were selected for in-depth interviews.The interview data was encoded by rooting theory,and five core categories of reading subject,reading environment,reading content,device perception and reading behavior were extracted.Combined with the technology acceptance model,construct a theoretical model of the influencing factors of audience deep reading behavior in the era of intelligent media.Finally,the data is collected by questionnaire,and the correlation analysis and regression analysis of the relevant data are carried out by SPSS to verify the rationality of the hypothesis model.It is found that self-efficacy,spatial environment and text quality have significant positive effects on perceptual usefulness and perceptual ease of use.Perceptual usefulness and perceptual ease of use have significant positive effects on deep reading behavior.And there are mediating effects between perceptual ease of use and perceptual ease of use on self-efficacy,spatial environment,text quality and deep reading behavior.The main contribution of this thesis is to combine intelligent technology and deep reading behavior to study,and put forward targeted suggestions to promote the formation and promotion of deep reading behavior habits in the era of intelligent media from the individual,spatial level,content level and technical level.Improve personal reading initiative and cultivate deep reading ability;focusing on library space reconstruction,create a smart space for in-depth reading;optimize digital reading content and promote high-quality reading resources;make rational use of emerging technologies and insist on taking the audience as the center.It provides a certain reference for solving the contradiction between new technology and deep reading in the era of intelligent media.
Keywords/Search Tags:the era of Intelligent Media, Digital Reading, Deep Reading, Technology Acceptance Model
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