Construction And Empirical Research On Reader Borrowing Index Of Academic Library

During the two sessions in 2012,13 CPPCC members jointly proposed the topic of quantify reading and emphasized the importance of introducing scientific reading evaluation methods to National Reading Project.Under the background of data science,university library is an important channel of National Reading Project.Digging deeply and quantifying library borrowing data will guide reading promotion work and improving users' borrowing behavior.Based on the theory of quantified self,this paper uses R language programming to obtain the borrowing data from university library.By the way of constructing the Borrowing Index to "quantify" the borrowing behavior of individual users.In order to guide and help individual users,it compares individual users with group users to analyze and position the borrowing level of individual users.The main research content includes two aspects: theoretical construction and empirical analysis.In theoretical construction,the Borrowing Index is defined as the indicator set to quantify the borrowing behavior of library readers,including 8 first-level indicators and 17 second-level indicators,such as the Activity,Burstiness,Memorability of users' borrowing behavior,as well as the Depth,Equilibrium,Universality,Novelty and Popularity of users' borrowing content.The indicators are all derived from the summary of historical documents and the logical reasoning of borrowing data.In empirical analysis,this paper takes more than 3.2 million borrowing data of the university library in the past 10 years as the research object and analyzes the data distribution characteristics of reader borrowing index from group users and individual users.Then it selects the representative user groups to provide a reference range of the Borrowing Index for individual users.The final results are reflected in User Borrowing Report for the library and User Borrowing Report for individual readers.The proposed innovations of this paper are as follows: 1.The Borrowing Index is proposed and constructed.It also verify the feasibility and guidance of the Borrowing Index by using the borrowing data of the university library.2.According to the data distribution characteristics of user borrowing frequency,a power law fitting method for user selection is proposed based on the classification standard of borrowing frequency conforming to power law distribution.3.Designed two versions of User Borrowing Report for the library and individual users,which can be generated automatically through the function of R Markdown.It can innovate the library data service mode.The results show that the Borrowing Index plays a guiding role in the borrowing behavior of users.The overall borrowing behavior of users shows the characteristics of low Activity,weak Burstiness and weak Memorability.The Depth,Equilibrium,Universality and Novelty of the borrowing content perform general.The distribution of Popularity is very uneven.Individual users can refer to the distribution characteristics of Borrowing Index of their own groups to accurately analyze their borrowing situation and find out shortcomings,so as to improve their reading behavior and make better use of the library.