Automated Classification to Improve the Efficiency of Weeding Library Collections

Previous studies have shown that weeding a library collection benefits patrons and increases circulation rates. However, the time required to review the collection and make weeding decisions presents a formidable obstacle. This study empirically evaluated methods for automatically classifying weeding candidates. A data set containing 80,346 items from a large-scale weeding project running from 2011 to 2014 at Wesleyan University was used to train six machine learning classifiers to predict a weeding decision of either ‘Keep’ or ‘Weed’ for each candidate. The study found statistically significant agreement (p?=?0.001) between classifier predictions and librarian judgments for all classifier types. The naive Bayes and linear support vector machine classifiers had the highest recall (fraction of items weeded by librarians that were identified by the algorithm), while the k-nearest-neighbor classifier had the highest precision (fraction of recommended candidates that librarians had chosen to weed). The variables found to be most relevant were: librarian and faculty votes for retention, item age, and the presence of copies in other libraries.     

Mandatory Student Fees and the Academic Library

As academic libraries' budgets remain flat while their expenditures rise, library leaders must seek out alternative sources of funding. One option is a mandatory student fee dedicated to the library. This article presents the results of a survey of 152 deans and directors of public R1 and R2 research universities that were asked whether their libraries benefit from mandatory student fees. While a library-specific fee is unusual, nearly half of responding libraries are eligible to receive some portion of another mandatory student fee. Study results can serve as evidence for libraries preparing to make a case for the significant, positive impact possible through even a modest library fee.     

The Methodological Foundations of Standardization in the Field of Library and Information Support of Science

This paper characterizes the methodological foundations of national standardization in the Russian Federation, in particular in the library and information field. The activities of Technical Standardization Committee 191 Scientific and Technical Information, Librarianship, and Publishing are reported.     

An Analytical Review of Global Ecoinformatics Problems

Modern global eco-dynamics problems are discussed. It is noted that global changes are mostly characterized by several key features, such as their multicomponent nature, as well as interactivity and nonlinearity. These features challenge various forecast estimates in such a way that the concept of forecasting has been replaced over the last few years by a much more ambiguous concept of scenarios. The vagueness of scenarios is due to the problem of global climate change. A global climate–nature–society system model is outlined.     

Russian Science Citation Index: Areas for Development Identified by Active Users

The current state of the Russian Science Citation Index is analyzed. Several areas for its further development identified by long-standing active users, such as data searching, refinement, and storage; current user alerts; data input with the Science Index license; patent information; and the application programming interface (API) are investigated.     

Narrative Persuasion in a New Media Environment: The Impact of Binge-Watching and Second-Screening

The study explored the role of second-screen use and binge-watching in moderating entertainment education (EE) effects. A pretest/posttest experiment of 273 viewers of East Los High measured the effects of exposure to three subplots, concerning alcohol abuse, abortion, and immigration. The effect of identification with characters on change in attitudes was significantly moderated by second-screen use and binge-watching. In particular, second-screening tended to enhance the positive impact of identification; whereas, among respondents who binge-watched the show, the effects of identification were weaker.     

Reasons for Student Engagement in Extra-Class Communication

This study extends instructional communication research on extra-class communication (ECC) by presenting an integrative analysis comparing the explanatory utility of student- and instructor-oriented reasons for student engagement in frequent ECC. Results from 495 college students suggested that student-oriented reasons, specifically the relational and functional student motives, were the only significant, positive predictors of students’ perceptions of frequent ECC engagement. Other student motives (excuse making, participation, sycophancy) and perceptions of instructor approachability did not significantly predict perceived frequency of ECC engagement.     

It’s More Than Self-Presentation: MUM Effects Can Reflect Private Discomfort and Concern for the Recipient

Is the reluctance to share bad news (i.e., the MUM effect) motivated more by a public display or private concern, and does it benefit mainly the messenger or the recipient? An experiment (N = 309) that crossed good/bad news with three communication channels (face-to-face, text messaging, e-mail) revealed that messenger reluctance was greatest under conditions of bad news and did not vary based on the channel through which the recipient contacted the messenger. In contrast with earlier work, this MUM effect was more consistent with a private fear of distressing the recipient. Theoretical implications and limitations are discussed.