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The purpose of this study is to document and analyze the success story of YouTube as a social network site in a competitive market, offering important academic and managerial implications.

Historical methods were used for investigation. This study applies the Resource-Advantage theory to identify key events in the history of YouTube from archival documents and evaluates and synthesizes the evidence to recount the channel’s evolution.

YouTube faced challenges from competitors across various industries since its launch. It has used its global user base and technological skills to develop innovative market offerings for users, contributors and marketers. YouTube built long-term relationships with stakeholders, continuously adapted to external changes and initiated internal alignments to compete in multiple industries. Over time, despite several changes in the competitive landscape, YouTube has grown into a successful media firm, competing across traditional broadcasting, gaming, live TV streaming and SNS industries. It is an exciting tale in the history of social networking.

This study significantly contributes to the marketing history of social network sites and platform-specific scholarship by applying the Resource-Advantage theory to document the evolution of YouTube.

Ovarian cancer (OC) is the most common type of gynecologic cancer in the world with a high rate of mortality. Due to manifestation of generic symptoms and absence of specific biomarkers, OC is usually diagnosed at a late stage. Machine learning models can be employed to predict driver genes implicated in causative mutations.

In the present study, a comprehensive next generation sequencing (NGS) analysis of whole exome sequences of 47 OC patients was carried out to identify clinically significant mutations. Nine functional features of 708 mutations identified were input into a machine learning classification model by employing the eXtreme Gradient Boosting (XGBoost) classifier method for prediction of OC driver genes.

The XGBoost classifier model yielded a classification accuracy of 0.946, which was superior to that obtained by other classifiers such as decision tree, Naive Bayes, random forest and support vector machine. Further, an interaction network was generated to identify and establish correlations with cancer-associated pathways and gene ontology data.

The final results revealed 12 putative candidate cancer driver genes, namely LAMA3, LAMC3, COL6A1, COL5A1, COL2A1, UGT1A1, BDNF, ANK1, WNT10A, FZD4, PLEKHG5 and CYP2C9, that may have implications in clinical diagnosis.

This paper aims to present recently published resources on library instruction and information literacy. It provides an introductory overview and a selected annotated bibliography of publications organized thematically and detailing, study populations, results and research contexts. The selected bibliography is useful to efficiently keep up with trends in library instruction for academic library practitioners, library science students and those wishing to learn about information literacy in other contexts.

This article annotates 340 English-language periodical articles, dissertations, theses and reports on library instruction and information literacy published in 2022. The sources were selected from the EBSCO platform for Library, Information Science and Technology Abstracts (LISTA), Education Resources Information Center (ERIC), Elsevier SCOPUS and ProQuest Dissertations and Theses. Sources selected were published in 2022 and included the terms “information literacy,” “library instruction,” or “information fluency” in the title, subject terms, or author supplied keywords. The sources were organized in Zotero. Annotations were made summarizing the source, focusing on the findings or implications. Each source was then thematically categorized and organized for academic librarians to be able to skim and use the annotated bibliography efficiently.

The paper provides a brief description of 340 sources from 144 unique publications, and highlights publications that contain unique or significant scholarly contributions. Further analysis of the sources and authorship are provided.

The information is primarily of use to academic librarians, researchers, and anyone interested as a quick and comprehensive reference to literature on library instruction and information literacy published within 2022.