Purpose/Significance: This article constructs a website classification model for academic library websites in Jiangsu. From a quantitative point of view, this paper uses a combination of decision tree algorithm and link analysis method in order to analyze how many categories academic library websites can be divided into? Which indicators can have a greater impact on academic library websites classification? And how the indicators are ranked according to importance. Method/Process: The link analysis method is used to collect the index data of academic library websites in Jiangsu. After the data is cleaned, the decision tree algorithm is used to analyze the data, and the classification decision tree model is constructed. Result/Conclusion: The result shows that academic library websites can be divided into four categories. PC word count, indexed monthly, and Baidu weight have an important influence on the construction of academic library websites’ decision tree. Among the various indicators, the impact of PC word count, mobile word count, Baidu weight, indexed monthly and the rest of others decrease in order.
Cite this paper
Liu, Q. and Xia, X. (2022). Construction of Classification Model of Academic Library Websites in Jiangsu Based on Decision Tree Algorithm and Link Analysis Method. Open Access Library Journal, 9, e8324. doi: http://dx.doi.org/10.4236/oalib.1108324.
Wang, Y., Zheng, Y.M., Jia, Y.M., et al. (2014) Research on the Development Strategy of ICT Resources for Education. Distance Education Magazine, 3-14.
Zheng, X.J. (2018) Analysis and Literature Review: The Interpretation of Educational Informatization 2.0 Action Plan (Part 1)—From the Perspective of Teachers in Vocational Colleges. Journal of Guangxi Vocational and Technical College, 51-61 2.
White, E. and King, L. (2021) Investigating the Development of a Research Portal as Part of an Academic Library Website for Scholarly Communication Guidance in a Public University in Ghana. International Information & Library Review, 53, 157-169.
https://doi.org/10.1080/10572317.2020.1805577
Desmarais, B. and Louderback, P. (2020) Planning and Assessing Patron Experience and Needs for an Academic Library Website. Journal of Library Administration, 60, 966-977. https://doi.org/10.1080/01930826.2020.1820283
Brunskill, A. (2020) “Without That Detail, I’m Not Coming”: The Perspectives of Students with Disabilities on Accessibility Information Provided on Academic Library Websites. College & Research Libraries, 81, 768-788.
https://doi.org/10.5860/crl.81.5.768
Liu, H.L. (2018) Investigation and Analysis of the Service Columns of Agricultural University Libraries—Taking 30 CALIS Agronomy Center Member Library Websites as Survey Objects. Henan Library Journal, 38, 105-108.
Wang, Z.J., Zhou, P. and Han, Z.B. (2013) Research on the Model of Competitor Recognition Based on Decision Tree Algorithm. Information Theory and Practice, 1-5 24.
Su, W., Jiang, F.F., Zhu, D.H., et al. (2015) Extraction of Maize Planting Area Based on Decision Tree and Mixed-Pixel Unmixing Methods. Journal of Agricultural Machinery, 289-295 301.
Huang, K.M., Fan, Z.J., Lu, S.J., et al. (2014) A Comparative Study of Chinese and American Think Tank Websites Based on Link Analysis. Information Theory and Practice, 129-133.
Cheng, H.Y. (2016) Comparative Research on My Country’s Science and Technology Media Websites—Taking Tiger Sniffing Network, Titanium Media and 36Kr as Examples. Journalism and Communication, 7-8.
