Search results

The 2020 Coronavirus pandemic forced universities to hastily transition to eLearning on a mass scale, necessitating the identification of populations who are more challenged by the transition. This study aims to identify how students’ level of introversion/extraversion and digital literacy come to play in their satisfaction with the eLearning environment.

The analysis examined 272 Israeli students who moved from a face-to-face learning environment to a Zoom learning environment between March–July 2020, following the outbreak of the pandemic. All the participants completed two rounds of surveys, and 62 of the 272 participants were then interviewed, and their social network was mapped using a sociogram.

Findings indicated that, in accordance with the “poor get richer” hypothesis, introverts expressed more satisfaction from the transition to the video-conferencing Zoom platform than extraverts. In addition, for highly introverted people, high digital literacy was significantly associated with increased course satisfaction, whereas for highly extraverted people, a high number of social ties with peers from the course was associated with course satisfaction.

As expected, the study’s findings shows that there is no “one size fits all” approach for online learning. Learners with different personalities can benefit from learning environments that foster greater satisfaction with the learning experience. Online platforms can, and should, be designed in a way that offers this needed personalization, and this study provides initial principles that can inform such personalization.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-01-2023-0028

Mental health literacy (MHL) is the ability to understand health information originating from different sources. Little is known about ethnic differences in sources for health information, and the effect these differences has on elderly MHL. In this paper, we focus on the social networks (i.e. social connections) of elderly people from different ethnic groups, and investigate the effect these networks have on MHL. Specifically, we focus on the ethnic diversity of one's peers (ethnic diversity) as a network characteristic that can interplay with his\her MHL.

The data used in this study were gathered using a survey among elderly (over the age of 60) Native Israeli Jews (N = 147) and Immigrant Jews from the Former Soviet Union (FSU, N = 131). The survey was used to assess our participants MHL, online and offline sources of mental health information and mental health service utilization. Interviews were also conducted with each participant. The interview purpose was to map the participants' social network (using a sociogram), while indicating the attributes of the participant's peers (age, gender, ethnicity, etc.) and the nature of the interaction (online vs. offline, strength of the tie, etc.). A set of hierarchal regression analyses were then used to examine which social network attributes are correlated with MHL levels.

Our findings shows that ethnic diversity within the social networks of Immigrants from the FSU contributed to their MHL more so than for native-born Jews. Specifically, face to face maintained connections with individuals from diverse ethnic groups lead to increased knowledge about how to search for mental health information. Online maintained connections with individuals from diverse ethnic groups, lead to increase attitudes that promote recognition of mental health related issues and appropriate help-seeking.

Understanding the interplay between the ethnic diversity among one's peers and his/her MHL offers an important additional prism of examining MHL; moving beyond the individual's characteristics and examining his/her social connections as well. The relevancy of these findings for reducing MHL inequalities between native-born and elderly migrants, as well as for ethnic minorities is discussed.

The purpose of this paper is to contribute to analyses of the sport-politics nexus by identifying whether the demographics of Twitter followers of Al-Jazeera Sport in the USA (rebranded in 2014 as beIN USA) can be associated with a specific political orientation.

Based on selective exposure theory, which posits that people follow news sources that reinforce their existing views, the authors identify the news outlets followed by beIN Twitter followers. To put the findings in perspective, the authors compared the results to the news outlets followed by the Twitter followers of Al-Jazeera America, Al-Jazeera’s second US outlet. Next, to understand the nature of the beIN and Al-Jazeera America communities, the authors used social network analysis to analyze the distribution of retweets within these communities.

The analysis shows that whereas Al-Jazeera America Twitter followers follow significantly more liberal than conservative news outlets, beIN’s followers were not identified with a specific political orientation. Analysis of beIN’s followers’ retweets shows a greater degree of connectivity among beIN’s followers than among the followers of Al-Jazeera America, indicating a more connected social network.

Findings indicate that beIN’s Twitter following is characterized by more diverse and more strongly connected audience than Al-Jazeera America on Twitter, highlighting sports as a non-politicized realm on Twitter.

For practitioners, the study illustrates that controversial non-western media networks such as Al-Jazeera can gain access to diverse populations in the West by operating in the sport realm rather than the news realm.

This study offers a pioneering indication of the extent of a sport-ethnocentrism nexus on Twitter.

Many studies have investigated how the structure of the collaborative networks of researchers influences the nature of their work, and its outcome. Co-authorship networks (CANs) have been widely looked at as proxies that can help bring understanding to the structure of research collaborative ties. The purpose of this paper is to provide a framework for describing what influences the formation of different research collaboration patterns.

The authors use social network analysis (SNA) to analyze the co-authorship ego networks of the ten most central authors in 24 years of papers (703 papers and 1,118 authors) published in the Proceedings of CASCON, a computer science conference. In order to understand what lead to the formation of the different CANs the authors examined, the authors conducted semi-structured interviews with these authors.

Based on this examination, the authors propose a typology that differentiates three styles of co-authorship: matchmaking, brokerage, and teamwork. The authors also provide quantitative SNA-based measures that can help place researchers’ CAN into one of these proposed categories. Given that many different network measures can describe the collaborative network structure of researchers, the authors believe it is important to identify specific network structures that would be meaningful when studying research collaboration. The proposed typology can offer guidance in choosing the appropriate measures for studying research collaboration.

The results presented in this paper highlight the value of combining SNA analysis with interviews when studying CAN. Moreover, the results show how co-authorship styles can be used to understand the mechanisms leading to the formation of collaborative ties among researchers. The authors discuss several potential implications of these findings for the study of research collaborations.