Mining library virtual reference service data by using the software NVivo 12

In the information age, virtual reference service (VRS) has gradually replaced the traditional face-to-face (F2F) reference and become an important way of reference for library users. Based on grounded theory, this research uses NVivo12 software to mine the virtual reference service data of users in the Sichuan University library, the first is high-frequency word analysis, and the second is mining the data by combining open coding, spindle coding, and selective coding. The analysis results of high-frequency words show that in the process of using various services of the library, the contents of the virtual reference service mainly focus on the following aspects: hours, literature resources, space, and facilities. The coding results show that the library virtual reference service data could be encoded into three core categories, they are "library spaces and facilities", "collections and electronic resources" and "services", where "library spaces and facilities" is the most concern aspect of the library users, which has 359 nodes, accounting for 50.71% of the total, and the proportion of "collections and electronic resources" and "Services" is not much different, 27.26% and 22.03%, respectively.