Highlights The study examines the factors leading to information avoidance during COVID-19 pandemic. Mass Media, Print Media and official websites are used for information seeking during the pandemic. Only Social Media exposure results in information overload and information anxiety. Information overload is strongly associated with information anxiety which gives rise to information avoidance. We extend the applicability of S-O-R model to the information behavior domain, especially during the uncertain times.

Purpose The purpose of this study is to examine the attitude of faculty members towards knowledge-sharing in the University of Education, Lahore. The impact of personal and organizational factors that may contribute to effective knowledge-sharing among the university’s teaching staff is also analyzed. The factors affecting the willingness of the faculty members to share knowledge are broadly classified as “organizational” and “personal” factors. Design/methodology/approach A questionnaire-based survey was conducted on permanent teaching staff working at different campuses of the University of Education all over the province of Punjab, Pakistan. The survey instrument for this study was adapted from four studies. The questionnaires were distributed among 246 faculty members personally. Findings The findings of the study showed that the faculty members were familiar with the importance of knowledge-sharing and were also interested in sharing their knowledge and expertise with others. The results showed that organizational factors (trust, reward system and organizational culture) played a vital role in enhancing the knowledge-sharing attitude of faculty members. The impact of these factors on knowledge-sharing attitude was significant. Originality/value This is the very first study which explored the personal and organizational factors of knowledge-sharing in a specific academic institution from Pakistan. The findings of the research provided useful insights to the management of the University of Education particularly and other universities in general to design strategies for enhancing knowledge-sharing culture in the higher education institution. These findings may also be helpful for other developing countries.

Purpose The purpose of this paper is to analyze the scientific collaboration of institutions and its impact on institutional research performance in terms of productivity and quality. The researchers examined the local and international collaborations that have a great impact on institutional performance. Design/methodology/approach Collaboration dependence measure was used to investigate the impact of an institution on external information. Based on this information, the authors used “index of gain in impact through collaboration” to find the impact of collaborated publications in institutional research performance. Bibliographic data between 1996 and 2010 retrieved from Scopus were used to conduct current study. The authors carried out the case study of top institutes of Pakistan in terms of publication count to elaborate the difference between high performing institutions and those who gain disproportionally in terms of perceived quality of their output because of local or international collaboration. Findings The results showed that the collaboration of developing countries institutes on international level had a great impact on institutional performance and they gain more benefit than local collaboration. Altogether, the scientific collaboration has a positive impact on institutional performance as measured by the cumulative source normalized impact per paper of their publications. The findings could also help researchers to find out appropriate collaboration partners. Originality/value This study has revealed some salient characteristics of collaboration in academic research. It becomes apparent that collaboration intensity is not uniform, but in general, the average quality of scientific production is the variable that most often correlates positively with the collaboration intensity of universities.

Self-disclosure on social networking sites (SNSs) leads to social capital development, connectedness, and relationship building. Due to several benefits associated with this behavior, self-disclosure has become a subject of research over the last few years. The current study investigates the antecedents of self-disclosure under the lens of the technology acceptance model (TAM). The research is quantitative, and the data were collected from 400 Pakistani Facebook users with a variety of demographic characteristics. The partial least squares-structural equation model (PLS-SEM) analysis technique was employed to analyze the data. The study′s findings confirmed that perceived usefulness is a strong predictor of personal information sharing, and it along with other variables causes a 31% variation in self-disclosure behavior. However, trust (medium and social) mediates the relationshipof perceived usefulness, privacy concerns, and self-disclosure behavior.

The present study, a part of researcher's Ph.D. project, aimed at exploring the reading trends of young Pakistani students (i.e., Generation Y: born during the 1980s and early 1990s, also known as internet generation), and the impact of digital media on their reading behavior. It was conducted as a pilot study on final year's master level students of the University of the Punjab. Quantitative research design, based on a survey was used. Convenient sampling technique was used to collect data from 50 students through questionnaire survey. It revealed that the students' reading behavior has been significantly changed during the last five years. Their overall reading time and digital reading time has been increased due to the availability of digital devices and digital reading material. The findings of this study are helpful in identifying the trends of reading behavior as well as in planning and designing library services with regard to the considering of the behavior of the students.

The purpose of the study is to (a) contribute to annotating an Altmetrics dataset across five disciplines, (b) undertake sentiment analysis using various machine learning and natural language processing–based algorithms, (c) identify the best-performing model and (d) provide a Python library for sentiment analysis of an Altmetrics dataset. First, the researchers gave a set of guidelines to two human annotators familiar with the task of related tweet annotation of scientific literature. They duly labelled the sentiments, achieving an inter-annotator agreement (IAA) of 0.80 (Cohen’s Kappa). Then, the same experiments were run on two versions of the dataset: one with tweets in English and the other with tweets in 23 languages, including English. Using 6388 tweets about 300 papers indexed in Web of Science, the effectiveness of employed machine learning and natural language processing models was measured by comparing with well-known sentiment analysis models, that is, SentiStrength and Sentiment140, as the baseline. It was proved that Support Vector Machine with uni-gram outperformed all the other classifiers and baseline methods employed, with an accuracy of over 85%, followed by Logistic Regression at 83% accuracy and Naïve Bayes at 80%. The precision, recall and F1 scores for Support Vector Machine, Logistic Regression and Naïve Bayes were (0.89, 0.86, 0.86), (0.86, 0.83, 0.80) and (0.85, 0.81, 0.76), respectively.

There appears a change in reading trends in the growing digital culture around the globe. The current research intended to identify the influence of this culture on the reading behaviour of young adults. A survey of final year Masters students from public and private sector universities in various knowledge domains (sciences and technology, social sciences, and arts and humanities) was conducted. The findings revealed a number of significant differences in both reading patterns and preferred reading formats among students of three knowledge domains. The findings suggest that all subjects should be treated separately when deciding on collection development and library services. This exploratory study proves that the digital environment creates a significant impact on individuals’ reading behaviour which needs to be considered by academics and library practitioners. It is a baseline study and opens many potential directions for future research.

Quality academic achievement is based on the development of good reading skills. Generally, reading is important for students to cope up with the evolving world of knowledge. Information and Communication Technologies (ICTs) have vastly influenced the reading practices of students. The younger generation of the information age spends most of their time in front of screens. Due to these drastic changes in the fabric of reading, generation Z is more likely to adopt e-reading. Therefore, an empirical investigation was carried out to explore the reading habits of generation Z students. For the study, a survey-based quantitative research design was applied. Data was collected through a structured questionnaire. The population included the students of two schools - one semi-government and one private higher secondary school of the Lahore district. The sample was selected purposively. Findings revealed that generation Z students prefer to read in paper form and in the English language. On average they read for up to four hours daily, preferably at home and mostly for academic purposes. They prefer print format, however, the advantages associated with e-reading motivate them to use electronic contents. One of the noteworthy findings is that libraries (academic/public) were their least preferred place for reading and obtaining reading material. The findings of the study would help parents, educators, and publishers to take necessary measures for promoting reading habits among students. The research findings would serve as a guideline for educationists to plan education policies according to the need and preferences of the future generation and for libraries to develop user-centered library services.