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The purpose of this study was to perform sentiment analysis and analyze the growth and popularity of Drupal, Joomla and WordPress on YouTube over a four-year period. This included identifying the most liked and commented videos for each content management system (CMS), ranking the CMSs based on the number of positive comments they received, and using natural language processing techniques to identify the top ten most frequently appearing words in videos about the CMSs.

The data for assessing the features of the videos of Drupal, WordPress and Joomla was extracted using Webometric Analyst version 4.4. with the help of the YouTube application programming interface key for videos on the selected CMSs uploaded from 2019 to 2022. The extraction of comments and sentiment analysis for the relevant videos was done using Mozdeh.

This study scrutinized 371, 234 and 313 videos of WordPress, Joomla and Drupal on YouTube. The findings reveal that there is a chronological growth of videos of the three CMSs in four years and till the present time, WordPress has the highest number of videos followed by Drupal and then Joomla. Regarding the ranking of highly liked videos, WordPress again wins the list with the highest number of likes in its videos followed by Drupal and then Joomla. For analyzing sentiments of the total comments extracted 123,409 for WordPress, 1,790 for Joomla and 1,783 for Drupal, respectively, WordPress receives the highest average positive comments followed by Drupal then Joomla. In top word frequency, the word “thank” highly occurs and viewers are asking for more tutorial videos.

To the best of the authors’ knowledge, this study is the first attempt for analyzing the sentiments of WordPress, Drupal and Joomla using Mozdeh software within the concerning period.

The purpose of this paper is to document how the library at Tecnológico de Monterrey, Monterrey Campus came to use the open source Drupal with other freely available tools as the basis for an extensible platform for current and future information discovery gateways.

After informal gathering of user opinions, formal usability testing of the current OPAC and Digital Library, and an evaluation of available options, Tecnológico de Monterrey's Library decided in October 2007 to build and test a prototype version of a new portal in April 2008, which after usability testing and interviews was improved and released for its users in June 2008.

The development team found out that Drupal, despite its steep learning curve, was a solid development platform which could achieve all the functionality the library set out to achieve through its freely available modules or custom, locally‐developed modules.

This paper documents the steps required to build an information discovery tool using Drupal and other freely available tools, thus demonstrating that Drupal is a viable and extensible development platform for libraries.

The purpose of this paper is to describe the benefits of integrating personalization within a library web site and presents methodology for achieving this goal within an academic setting.

The project documented in this study explores the use of student course enrollment data as the basis for creating a personalized library web site. Off-the-shelf, open source applications are used in conjunction with existing university data to deliver a final product that offers an enhanced user experience for the university community.

Adaptive personalization is increasingly commonplace on the web. Academic libraries have a unique source of existing data that offers the potential of adding personalization to the library web site. At present, the personalization of library online services remains largely unexplored. This project illustrates one relatively low-cost method to help libraries interested in creating personalized web sites.

This paper provides a guide for libraries interested in the implementation of personalization within their web sites.

The project described in this case study is highly unique within libraries. The paper outlines the feasibility and technical requirements associated with using course enrollment data to add personalized content to a library web site.

The purpose of this paper is to detail a Library open source software (OSS) development project resulting in the launch of StatBase, a statistical gathering and data visualization tool, so that organizations can adopt a locally managed alternative to costly data aggregation tools.

This case study is based on a literature review, Agile development framework, and user experience modeling. The software solution features a Joomla framework with contributed modules and open source architecture.

This case study demonstrates the creation and practical implementation of a scalable OSS platform for data management and analysis.

Provides a frame of reference and methodology for libraries, both public and academic, seeking to implement a web-based resource to gather, organize, and interpret statistical metrics via a centralized, lightweight, open source architecture.

This case study provides a detailed scope and step-by-step technology process description by which an organization can adopt or model the StatBase solution for business metrics.

This paper aims to take seriously the import accorded to the interface within the digital humanities. It will probe some of the possibilities and limits of the computer interface as a reading and research tool by unpacking theoretical and practical aspects of interface design.

The authors wanted to see if they could design a tool that would meet three interrelated goals: the first was to develop a digital tool that would enable scholarship rather than mere publishing. Next, they wanted to build an interface that would acknowledge the situatedness of reading and meaning-making practices.

The research-oriented design approach to interface design has shown us how valuable it is to combine research and practice when thinking through issues in the digital humanities. Engaging in such a design project provides the unique opportunity to bring together theoretical concepts relating interface design with robust tools like XML mark-up and Drupal modules.

There is literature on the subject of transformation of print documents to electronic text (Hayles, 2003) and the representation of text within a computer (Sperberg-McQueen, 1991); this project attempts to build a prototype of what these theories might look like.

Researchers at the University of Tennessee Libraries experimented with crowdsourcing to determine if contributions by members of the public could be utilized to add citations and subject tags to a new online bibliography, Database of the Smokies (DOTS: dots.lib.utk.edu). The paper aims to discuss this issue.

The database is built in Drupal, an open source platform that provides a crowdsourcing mechanism. The public was offered the opportunity to create accounts and add content to DOTS. After three months, the project team performed a transaction log analysis of user submissions in order to determine whether an editorial process was necessary.

This analysis revealed that 18 percent of database content was the result of crowdsourcing and that much of the content submitted by participants was either obscure or difficult to locate. The analysis also showed that while contributors added valuable citations, an editorial review process was necessary to ensure this crowdsourced content could be published in the database. In addition, contributor supplied subject tags were not of significant uniqueness or quantity to substantially influence the existing taxonomy. Finally, the publicity of the crowdsourcing feature allowed other institutions to contribute to the project and add rare material.

This paper offers a model for utilizing crowdsourcing to entice a sophisticated user group to help build a bibliographic database.

Effective and efficient software security inspection is crucial as the existence of vulnerabilities represents severe risks to software users. The purpose of this paper is to empirically evaluate the potential application of Stochastic Gradient Boosting Trees (SGBT) as a novel model for enhanced prediction of vulnerable Web components compared to common, popular and recent machine learning models.

An empirical study was conducted where the SGBT and 16 other prediction models have been trained, optimized and cross validated using vulnerability data sets from multiple versions of two open-source Web applications written in PHP. The prediction performance of these models have been evaluated and compared based on accuracy, precision, recall and F-measure.

The results indicate that the SGBT models offer improved prediction over the other 16 models and thus are more effective and reliable in predicting vulnerable Web components.

This paper proposed a novel application of SGBT for enhanced prediction of vulnerable Web components and showed its effectiveness.