scholarly journals From Social Networks to Publishing Platforms: A Review of the History and Scholarship of Academic Social Network Sites

2019 ◽  
Vol 6 ◽  
Author(s):  
Katy Jordan
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Sites ◽  
Academic Social Network

scholarly journals Academic Social Networks: How the web is changing our way to make and communicate researches

2015 ◽  
Vol 7 (2) ◽  
pp. 3-14 ◽  
Author(s):  
Giovanni Bonaiuti
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Sites ◽  
Rapid Evolution ◽  
Scientific Field ◽  
Academic Social Network ◽  
Academic Social Networks ◽  
Insight Into ◽  
The Web ◽  
Natural Component

Abstract Networking is not only essential for success in academia, but it should also be seen as a natural component of the scholarly profession. Research is typically not a purely individualistic enterprise. Academic social network sites give researchers the ability to publicise their research outputs and connect with each other. This work aims to investigate the use done by Italian scholars of 11/D2 scientific field. The picture presented shows a realistic insight into the Italian situation, although since the phenomenon is in rapid evolution results are not stable and generalizable.

scholarly journals IMPACT OF OFFLINE AND ONLINE SOCIAL NETWORKS ON LONELINESS AND MENTAL HEALTH AMONG ITALIAN OLDER PEOPLE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S529-S529
Author(s):  
Daniele Zaccaria ◽  
Georgia Casanova ◽  
Antonio Guaita
Keyword(s):  
Mental Health ◽  
Social Networks ◽  
Social Network ◽  
Older People ◽  
Online Social Networks ◽  
Social Network Sites ◽  
Well Being ◽  
Controlled Study ◽  
Face To Face ◽  
Causal Impact

Abstract In the last decades the study of older people and social networks has been at the core of gerontology research. The literature underlines the positive health effects of traditional and online social connections and also the social networks’s positive impact on cognitive performance, mental health and quality of life. Aging in a Networked Society is a randomized controlled study aimed at investigating causal impact of traditional face-to-face social networks and online social networks (e.g. Social Network Sites) on older people’ health, cognitive functions and well-being. A social experiment, based on a pre-existing longitudinal study (InveCe - Brain Aging in Abbiategrasso) has involved 180 older people born from 1935 to 1939 living in Abbiategrasso, a municipality near Milan. We analyse effects on health and well-being of smartphones and Facebook use (compared to engagement in a more traditional face-to-face activity), exploiting the research potential of past waves of InveCe study, which collected information concerning physical, cognitive and mental health using international validate scale, blood samples, genetic markers and information on social networks and socio-demographic characteristics of all participants. Results of statistical analysis show that poor social relations and high level of perceived loneliness (measured by Lubben Scale and UCLA Loneliness scale) affect negatively physical and mental outcomes. We also found that gender and marital status mediate the relationship between loneliness and mental wellbeing, while education has not significant effect. Moreover, trial results underline the causal impact of ICT use (smartphones, internet, social network sites) on self-perceived loneliness and cognitive and physical health.

Gender Differences in the Technology’s Classic Models in Social Network Sites

2014 ◽  
pp. 126-142
Author(s):  
Begoña Peral-Peral ◽  
Ángel F. Villarejo-Ramos ◽  
Manuel J. Sánchez-Franco
Keyword(s):  
Gender Differences ◽  
Social Networks ◽  
Social Network ◽  
Technology Acceptance ◽  
Information And Communication Technologies ◽  
Social Network Sites ◽  
Communication Technologies ◽  
Internet Users ◽  
Information And Communication ◽  
Acceptance Model

Social Network Sites (SNS) have very rapidly become part of the daily reality of Internet users in recent years. Firms also use social networks as a two-way communication with their current and potential customers. This exploratory work means to analyze if Internet users’ gender influences the behavior of using social networks. There is a reason for this. Despite Information and Communication Technologies (ICT) acceptance and use being more frequent in men, according to the previous literature, in line with different surveys on the subject, social networks are more used by women. The authors, therefore, analyze in this chapter if there are gender differences in the constructs of technology’s classic models, such as the TAM (Technology Acceptance Model) and the TPB (Theory of Planned Behavior). They use a sample of 1,460 university students.

Development of Adaptive Social Network Based on Learners' Thinking and Learning Styles

2018 ◽  
pp. 90-107
Author(s):  
Mahnane Lamia ◽  
Hafidi Mohamed
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Learning Styles ◽  
Learning Experience ◽  
Social Network Sites ◽  
Innovative Approach ◽  
Thinking Styles ◽  
New Approach ◽  
Learning Content ◽  
Web Learning

Adaptive social network sites (ASNS) are an innovative approach to a web learning experience delivery. They try to solve the main shortcomings of classical social networks—“one-size-fits-all” approach and “lost-in-hyperspace” phenomena—by adapting the learning content and its presentation to needs, goals, thinking styles, and learning styles of every individual learner. This chapter outlines a new approach to automatically detect learners' thinking and learning styles, and takes into account that thinking and learning styles may change during the learning process in unexpected and unpredictable ways. The approach is based on the Felder learning styles model and Hermann thinking styles model.

Ascertaining Trust Indicators in Social Networking Sites

2013 ◽  
Vol 3 (2) ◽  
pp. 22-37
Author(s):  
N. Veerasamy ◽  
W. A. Labuschagne
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking ◽  
Social Networking Sites ◽  
Social Network Sites ◽  
Specific Focus

The use of social network sites has exploded with its multitude of functions which include posting pictures, interests, activities and establishing contacts. However, users may be unaware of the lurking dangers of threats originating from Social Networking Sites (SNS) which include malware or fake profiles. This paper investigates the indicators to arouse suspicion that a social networking account is invalid with a specific focus on Facebook as an illustrative example. The results from a survey on users’ opinions on social networks, is presented in the paper. This helps reveal some of the trust indicators that leads users to ascertaining whether a social networking profile is valid or not. Finally, indicators of potentially deceptive agents and profiles are given as a guideline to help users decide whether they should proceed with interaction with certain contacts.

scholarly journals A MODEL TO CLASSIFY USERS OF SOCIAL NETWORKS BASED ON PAGERANK

2012 ◽  
Vol 22 (07) ◽  
pp. 1250162 ◽  
Author(s):  
FRANCISCO PEDROCHE
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Explicit Expression ◽  
Social Network Sites ◽  
Step Process ◽  
Pagerank Algorithm

In this paper, we present a model to classify users of Social Networks. In particular, we focus on Social Network Sites. The model is based on the PageRank algorithm. We use the personalization vector to bias the PageRank to some users. We give an explicit expression of the personalization vector that allows the introduction of some typical features of the users of SNSs. We describe the model as a seven-step process. We illustrate the applicability of the model with two examples. One example is based on real links of a Facebook network. We also indicate how to take into account real actions of Facebook users to implement the model.

Interest-oriented versus relationship-oriented social network sites in China

First Monday ◽  
2010 ◽  
Author(s):  
Weiyu Zhang ◽  
Rong Wang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Structural Analysis ◽  
Collective Action ◽  
Social Ties ◽  
Social Network Sites ◽  
Design Features ◽  
The Social ◽  
Different Types ◽  
Common Interests

This paper examines interest-oriented vs. relationship-oriented social network sites in China and their different implications for collective action. By utilizing a structural analysis of the design features and a survey of members of the social networks, this paper shows that the way a social network site is designed strongly suggests the formation and maintenance of different types of social ties. The social networks formed among strangers who share common interests imply different types of collective action, compared to the social networks that aim at the replication and strengthening of off-line relationships.

The cost of (anti-) social networks: Identity, agency and neo-luddites

First Monday ◽  
2006 ◽  
Author(s):  
Ryan Bigge
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking ◽  
Social Networking Sites ◽  
Media Coverage ◽  
Social Network Sites ◽  
Technological Determinism ◽  
Theoretical Approaches ◽  
The Media ◽  
The Cost

The media coverage and resultant discourse surrounding social networking sites such as Facebook, MySpace and Friendster contain narratives of inevitability and technological determinism that require careful explication. Borrowing a tactic from the Russian Futurists, this paper attempts to make strange (that is, to defamiliarize) social network sites and their associated discourses by drawing upon an eclectic but interrelated set of metaphors and theoretical approaches, including: the digital enclosure, network sociality, socio-technical capital and Steven Jones’s recent examination of neo-Luddites. Whenever appropriate, this paper will integrate relevant magazine and newspaper journalism about social networking sites.

scholarly journals Co-authorship prediction in academic social network

2019 ◽  
Author(s):  
William Takahiro Maruyama ◽  
Luciano Antonio Digiampietri
Keyword(s):  
Artificial Intelligence ◽  
Social Networks ◽  
Social Network ◽  
State Of The Art ◽  
The State ◽  
Artificial Intelligence Techniques ◽  
Academic Social Network ◽  
Academic Social Networks

The prediction of relationships in a social network is a complex and extremely useful task to enhance or maximize collaborations by indicating the most promising partnerships. In academic social networks, prediction of relationships is typically used to try to identify potential partners in the development of a project and/or co-authors for publishing papers. This paper presents an approach to predict coauthorships combining artificial intelligence techniques with the state-of-the-art metrics for link predicting in social networks.

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