Analysis of Academic Libraries' Facebook Posts: Text and Data Analytics

This research analyzed a dataset of academic libraries' posts on Facebook. It applied a text and data analytics approach to a dataset collected from the Facebook posts of academic libraries at the top 100 English-speaking universities, as listed by the 2014 Shanghai World University Rankings. The dataset is from a two-year posting history of 18,333 unique posts, 113,621 likes, and 3401 comments. Less than a quarter of the libraries had more than 2000 post-related likes, and only seven received more than 100 comments on their postings. Content analysis identified the most prevalent single word (unigrams), bigrams (two-word sequences), and trigrams (three-word sequences) in high and low engagement content. Semantic analysis identified the semantic categories for posts with high and low engagement. The findings can assist academic libraries in their social media strategies for engagement, marketing, and visibility.     

Institutional policy process improvement: using structurating activity theory to inform practice

Organizational communication scholars are increasingly called upon to use theoretical knowledge to address problematic processes in public institutions. This article reports a process improvement project focused on a university conflict of interest (COI) policy as an example of how scholars can engage theory to improve ongoing policy processes. The project team included communication scholars and research administration staff who designed, implemented, and evaluated the mixed-methods project guided by structurating activity theory. Baseline survey results were used to design the process improvement project. Results of the follow-up survey indicate that researchers who participated in some aspect of the process improvement project (i.e. attending a policy café, using the redesigned website, or reading the new Quick Reference Guide) reported higher levels of policy communication and knowledge and more positive attitudes toward the COI policy than researchers who had not engaged with process improvement efforts. We offer theoretical and practical implications of results for organizational communication scholars and practitioners.     

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.     

Alexa,Siri, Cortana,and More: An Introduction to Voice Assistants

Voice assistants are software agents that can interpret human speech and respond via synthesized voices. Apple’s Siri, Amazon’s Alexa, Microsoft’s Cortana, and Google’s Assistant are the most popular voice assistants and are embedded in smartphones or dedicated home speakers. Users can ask their assistants questions, control home automation devices and media playback via voice, and manage other basic tasks such as email, to-do lists, and calendars with verbal commands. This column will explore the basic workings and common features of today’s voice assistants. It will also discuss some of the privacy and security issues inherent to voice assistants and some potential future uses for these devices. As voice assistants become more widely used, librarians will want to be familiar with their operation and perhaps consider them as a means to deliver library services and materials.     

Investigating married adults’ communal coping with genetic health risk and perceived discrimination

Increased genetic testing in personalized medicine presents unique challenges for couples, including managing disease risk and potential discrimination as a couple. This study investigated couples’ conflicts and support gaps as they coped with perceived genetic discrimination. We also explored the degree to which communal coping was beneficial in reducing support gaps and ultimately stress. Dyadic analysis of married adults (N?=?266, 133 couples), in which one person had the genetic risk for serious illness, showed that perceived discrimination predicted more frequent conflicts about alpha-1 antitrypsin deficiency-related treatment, privacy boundaries, and finances, which, in turn, predicted wider gaps in emotion and esteem support, and greater stress for both spouses. Communal coping predicted lower support gaps for both partners and marginally lower stress.     

Critical communication pedagogy and service learning in a mixed-method communication research course

ABSTRACT

Course: Mixed-Method Communication Research Methods

Objective: The purpose of this semester-long activity is to provide students with opportunities to cultivate mixed-method communication research skills through a social justice-informed service-learning format. Completing this course, students will be able to: recognize the unique strengths of quantitative and qualitative research methods; locate, evaluate, and utilize scholarly literature for a literature review; conduct an original research project using quantitative and qualitative research methods to gather and analyze data; and raise self and community awareness about a social issue through collaboration with a community organization.     

Circulating Cell-Free DNA Level in Prediction of COVID-19 Severity and Mortality: Correlation of with Haematology and Serum Biochemical Parameters

Lymphocyte dysregulation in coronavirus disease-19 (COVID-19) is a major contributing factor linked to disease severity and mortality. Apoptosis results in the accumulation of cell-free DNA (cfDNA) in circulation. COVID-19 has a heterogeneous clinical course. The role of cfDNA levels was studied to assess the severity and outcome of COVID-19 patients and correlated with other laboratory parameters. The current case series included 100 patients with mild COVID-19 (MCOV-19) and 106 patients with severe COVID-19 (SCOV-19). Plasma cfDNA levels were quantified using SYBR green quantitative real-time PCR through amplification of the β-actin gene. CfDNA level was significantly higher in SCOV-19 at 706.7 ng/ml (522.6–1258) as compared to MCOV-19 at 219.8 ng/ml (167.7–299.6). The cfDNA levels were significantly higher in non-survivor than in survivors (p = 0.0001). CfDNA showed a significant correlation with NLR, ferritin, LDH, procalcitonin, and IL-6. The diagnostic sensitivity and specificity of cfDNA in the discrimination of SCOV-19 from MCOV-19 were 90.57% & 80%, respectively. CfDNA showed a sensitivity of 94.74% in the differentiation of non-survivors from survivors. CfDNA levels showed a significant positive correlation with other laboratory and inflammatory markers of COVID-19. CfDNA levels, NLR, and other parameters may be used to stratify and monitor COVID-19 patients and predict mortality. CfDNA may be used to predict COVID-19 severity with higher diagnostic sensitivity.