Social Network Analysis Using Author Co-Citation Data

This study examines the social network of scholars in the field of Communication by using author co-citation data. A matrix containing the number of co-cited documents between pairs of authors is created for social network analysis of scholars who are on the editorial board of Journal of Communication, and the networked map of the scholars is used to visualize the knowledge structure of the field by identifying groups of authors who are more central than others. Social Science Citation Index (SSCI) is used to collect the author co-citation data, and UCInet is employed for social network analysis as well as network visualization

Identifying Vaccine Hesitant Communities on Twitter and their Geolocations: A Network Approach

Vaccine misinformation online may contribute to the increase of anti-vaccine sentiment and vaccine-hesitant behaviors. Social network data was used to identify Twitter vaccine influencers, their online twitter communities, and their geolocations to determine pro-vaccine and vaccine-hesitant online communities. We explored 139,433 tweets and identified 420 vaccine Twitter influencers—opinion leaders and assessed 13,487 of their tweets and 7,731 of their connections. Semantic network analysis was employed to determine twitter conversation themes. Results suggest that locating social media influencers is an efficient way to identify and target vaccine-hesitant communities online. We discuss the implications of using this process for public health education and disease management

Mapping Articles on China in Wikipedia: An Inter-Language Semantic Network Analysis

This article describes an inter-language semantic network analysis examining the differences between articles about China in the Chinese and English versions of Wikipedia. It explores the differences in the content of Wikipedia through (a) correlation analysis of semantic networks and (b) the salience of semantic concepts through their network centralities. The results suggest there is high dissimilarity between the semantic content of the English and Chinese versions of articles on China. While both pages focused on government, population, language, character, diplomatic relations, development of the economy, and science and technology, the Chinese-speaking and English-speaking contributors framed the article on China differently—according to dissimilarities in cultures, values, interests, situations, and emotions of different language groups. This research contributes to the literature and understanding of how culture of different language groups influences the process of crowdsourcing knowledge on online collaboration platforms

The use of myelinating cultures as a screen of glycomolecules for CNS repair

In vitro cell-based assays have been fundamental in modern drug discovery and have led to the identification of novel therapeutics. We have developed complex mixed central nervous system (CNS) cultures, which recapitulate the normal process of myelination over time and allow the study of several parameters associated with CNS damage, both during development and after injury or disease. In particular, they have been used as a reliable screen to identify drug candidates that may promote (re)myelination and/or neurite outgrowth. Previously, using these cultures, we demonstrated that a panel of low sulphated heparin mimetics, with structures similar to heparan sulphates (HSs), can reduce astrogliosis, and promote myelination and neurite outgrowth. HSs reside in either the extracellular matrix or on the surface of cells and are thought to modulate cell signaling by both sequestering ligands, and acting as co-factors in the formation of ligand-receptor complexes. In this study, we have used these cultures as a screen to address the repair potential of numerous other commercially available sulphated glycomolecules, namely heparosans, ulvans, and fucoidans. These compounds are all known to have certain characteristics that mimic cellular glycosaminoglycans, similar to heparin mimetics. We show that the N-sulphated heparosans promoted myelination. However, O-sulphated heparosans did not affect myelination but promoted neurite outgrowth, indicating the importance of structure in HS function. Moreover, neither highly sulphated ulvans nor fucoidans had any effect on remyelination but CX-01, a low sulphated porcine intestinal heparin, promoted remyelination in vitro. These data illustrate the use of myelinating cultures as a screen and demonstrate the potential of heparin mimetics as CNS therapeutics

A comparison of three methods to determine the subject matter in textual data

This study compares three different methods commonly employed for the determination and interpretation of the subject matter of large corpuses of textual data. The methods reviewed are: (1) topic modeling, (2) community or group detection, and (3) cluster analysis of semantic networks. Two different datasets related to health topics were gathered from Twitter posts to compare the methods. The first dataset includes 16,138 original tweets concerning HIV pre-exposure prophylaxis (PrEP) from April 3, 2019 to April 3, 2020. The second dataset is comprised of 12,613 tweets about childhood vaccination from July 1, 2018 to October 15, 2018. Our findings suggest that the separate “topics” suggested by semantic networks (community detection) and/or cluster analysis (Ward's method) are more clearly identified than the topic modeling results. Topic modeling produced more subjects, but these tended to overlap. This study offers a better understanding of how results may vary based on method to determine subject matter chosen

An introduction to Elinor Glyn : her life and legacy

This special issue of Women: A Cultural Review re-evaluates an author who was once a household name, beloved by readers of romance, and whose films were distributed widely in Europe and the Americas. Elinor Glyn (1864–1943) was a British author of romantic fiction who went to Hollywood and became famous for her movies. She was a celebrity figure of the 1920s, and wrote constantly in Hearst's press. She wrote racy stories which were turned into films—most famously, Three Weeks (1924) and It (1927). These were viewed by the judiciary as scandalous, but by others—Hollywood and the Spanish Catholic Church—as acceptably conservative. Glyn has become a peripheral figure in histories of this period, marginalized in accounts of the youth-centred ‘flapper era’. Decades on, the idea of the ‘It Girl’ continues to have great pertinence in the post-feminist discourses of the twenty-first century. The 1910s and 1920s saw the development of intermodal networks between print, sound and screen cultures. This introduction to Glyn's life and legacy reviews the cross-disciplinary debate sparked by renewed interest in Glyn by film scholars and literary and feminist historians, and offers a range of views of Glyn's cultural and historical significance and areas for future research

Experiences of learning through collaborative evaluation from a masters programme in professional education

This paper presents findings from a collaborative evaluation project within a masters programme in professional education. The project aimed to increase knowledge of research methodologies and methods through authentic learning where participants worked in partnership with the tutor to evaluate the module which they were studying. The project processes, areas of the course evaluated and the data collection methods are outlined. The findings focus on key themes from evaluating the effectiveness of using a collaborative evaluation approach, including: enhanced student engagement; creativity of the collaborative evaluation approach; equality between the tutor and students; and enhanced research skills. Discussion focuses on the outcomes and effectiveness of the project and tutor reflections on adopting a collaborative approach. This paper highlights lessons from the project relevant to those interested in staff-student partnership approaches and those facilitating postgraduate learning and teaching programmes and educational research courses

MyelinJ: an ImageJ macro for high throughput analysis of myelinating cultures

MyelinJ is a free user friendly ImageJ macro for high throughput analysis of fluorescent micrographs such as 2D-myelinating cultures and statistical analysis using R. MyelinJ can analyse single images or complex experiments with multiple conditions, where the ggpubr package in R is automatically used for statistical analysis and the production of publication quality graphs. The main outputs are percentage (%) neurite density and % myelination. % neurite density is calculated using the normalise local contrast (NLC) algorithm, followed by thresholding, to adjust for differences in intensity. For % myelination the myelin sheaths are selected using the Frangi vesselness algorithm, in conjunction with a grey scale morphology filter and the removal of cell bodies using a high intensity mask. MyelinJ uses a simple graphical user interface and user name system for reproducibility and sharing that will be useful to the wider scientific community that study 2D-myelination in vitro