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The present review is an endeavour to understand the use of Academic Social Networking (ASN) sites by academics and researchers during the 2001-2020. The literature indicates existence of disciplinary differences in choice of ASN platforms as well as frequency of use of a particular platform by users belonging to a particular discipline. The strong disciplinary influence could be attributed to variations in social and cultural practices of a particular discipline. The review finds professional visibility as one of the outstanding motivating factors for academics and researchers to join ASN sites. Seeking scholarly answer, accruing citations, seeking expert, sharing research literature by availing self-archiving facilities of ASN sites, exploring collaborative research avenues and job seeking are some other important motivators. The review noticed that alternative metrics have become a strong contender for measuring research impact. The review also found age and gender discrimination, snooping, academic cyber bullying, flooding of ASN sites with substandard literature as some concerns which need concerted attention and suggests more research in these fronts and accordingly modification of ASN interfaces to make them more responsive to user's needs. [ABSTRACT FROM AUTHOR]

In this era of digital transformation, when the amount of scholarly literature is rapidly growing, hundreds of papers are published online daily with regard to different fields, especially in relation to academic subjects. Therefore, it difficult to find an expert/author to collaborate with from a specific research area. This is thought to be one of the most challenging activities in academia, and few people have considered authors' multi-factors as an enhanced method to find potential collaborators or to identify the expert among them; consequently, this research aims to propose a novel model to improve the process of recommending authors. This is based on the authors' similarity measurements by extracting their explicit and implicit topics of interest from their academic literature. The proposed model mainly consists of three factors: author-selected keywords, the extraction of a topic's distribution from their publications, and their publication-based statistics. Furthermore, an enhanced approach for identifying expert authors by extracting evidence of expertise has been proposed based on the topic-modeling principle. Subsequently, an interactive network has been constructed that represents the predicted authors' collaborative relationship, including the top-k potential collaborators for each individual. Three experiments have been conducted on the collected data; they demonstrated that the most influential factor for accurately recommending a collaborator was the topic's distribution, which had an accuracy rate of 88.4%. Future work could involve building a heterogeneous co-collaboration network that includes both the authors with their affiliations and computing their similarities. In addition, the recommendations would be improved if potential and real collaborations were combined in a single network. [ABSTRACT FROM AUTHOR]

A survey of scholars in mass communication and related disciplines found that the academic social network ResearchGate is a popular platform for following like-minded academics, sharing one's work, locating relevant research, and managing one's academic reputation, in addition to gratifying more traditional social media needs, such as information seeking, social interaction, and even entertainment. The analysis revealed that academics who are extrinsically motivated to conduct research update their accounts more frequently but extract fewer benefits from the platform. Moreover, respondents agree that the RG Score generated by the social platform is not an accurate metric for one's research impact. [ABSTRACT FROM AUTHOR]

Altmetrics are a relatively new phenomenon in research. These metrics measure the attention that research articles receive from nontraditional venues such as social media and the Internet. This study examined how these metrics affect both the readership and citation of articles in communication research. The study examined citation data alongside altmetrics data from academic social networking sites ResearchGate and Mendeley, as well as mentions on Facebook, Twitter, and Google+. Results indicated that all altmetrics positively correlated with citation. Posting articles on sites such as ResearchGate and Mendeley not only impacted readership, it increased the likelihood of citation. Other variables that improved readership and citation were social media mentions, downloadable articles, coauthorship, and an active online presence among scholars. [ABSTRACT FROM AUTHOR]

In this era of digital transformation, when the amount of scholarly literature is rapidly growing, hundreds of papers are published online daily with regard to different fields, especially in relation to academic subjects. Therefore, it difficult to find an expert/author to collaborate with from a specific research area. This is thought to be one of the most challenging activities in academia, and few people have considered authors’ multi-factors as an enhanced method to find potential collaborators or to identify the expert among them; consequently, this research aims to propose a novel model to improve the process of recommending authors. This is based on the authors’ similarity measurements by extracting their explicit and implicit topics of interest from their academic literature. The proposed model mainly consists of three factors: author-selected keywords, the extraction of a topic’s distribution from their publications, and their publication-based statistics. Furthermore, an enhanced approach for identifying expert authors by extracting evidence of expertise has been proposed based on the topic-modeling principle. Subsequently, an interactive network has been constructed that represents the predicted authors’ collaborative relationship, including the top-k potential collaborators for each individual. Three experiments have been conducted on the collected data; they demonstrated that the most influential factor for accurately recommending a collaborator was the topic’s distribution, which had an accuracy rate of 88.4%. Future work could involve building a heterogeneous co-collaboration network that includes both the authors with their affiliations and computing their similarities. In addition, the recommendations would be improved if potential and real collaborations were combined in a single network.

Purpose – The purpose of this paper is twofold. First, the study aims to investigate the relationship between the altmetric indicators from ResearchGate (RG) and the bibliometric indicators from the Scopus database. Second, the study seeks to examine the relationship amongst the RG altmetric indicators themselves. RG is a rich source of altmetric indicators such as Citations, RGScore, Impact Points, Profile Views, Publication Views, etc. Design/methodology/approach – For establishing whether RG metrics showed the same results as the established sources of metrics, Pearson’s correlation coefficients were calculated between the metrics provided by RG and the metrics obtained from Scopus. Pearson’s correlation coefficients were also calculated for the metrics provided by RG. The data were collected by visiting the profile pages of all the members who had an account in RG under the Department of Physics, Panjab University, Chandigarh (India). Findings – The study showed that most of the RG metrics showed strong positive correlation with the Scopus metrics, except for RGScore (RG) and Citations (Scopus), which showed moderate positive correlation. It was also found that the RG metrics showed moderate to strong positive correlation amongst each other. Research limitations/implications – The limitation of this study is that more and more scientists and researchers may join RG in the future, therefore the data may change. The study focuses on the members who had an account in RG under the Department of Physics, Panjab University, Chandigarh (India). Perhaps further studies can be conducted by increasing the sample size and by taking a different sample size having different characteristics. Originality/value – Being an emerging field, not much has been conducted in the area of altmetrics. Very few studies have been conducted on the reach of academic social networks like RG and their validity as sources of altmetric indicators like RGScore, Impact Points, etc. The findings offer insights to the question whether RG can be used as an alternative to traditional sources of bibliometric indicators, especially with reference to a rapidly developing country such as India. [ABSTRACT FROM AUTHOR]

Academic social networking (ASN) sites are becoming a popular communication medium among scholars. This case study was designed to explore communication behaviors of physicists, linguists, and sociologists on an ASN site called Academia.edu, their motivations for using it, and the perceived impact of their use of the site on their professional activities. Results from this study are valuable for designing computer-mediated and web-based communication media for scholars and also for adding richness to the literature related to scholarly communication. For the purpose of this study, data was collected using three different instruments: Server log, survey, and interview. Data used for analyses included a total of 20,309 server log data, 267 survey responses, and 28 interviews from scholars of Physics, Sociology, and Linguistics who use Academia.edu. Results from the study showed that the use of Academia.edu is dependent on the discipline scholars are affiliated with, their professional status, and the time of the year. Unlike physicists, linguists and sociologists are more inclined to using Academia.edu and other ASN sites. Although linguists and sociologists actively use Academia.edu, their motivations to use the site are different. These differences in user-motivations and user-activities across the disciplines are influenced by variations in the social and cultural practices of the disciplines. This study used Whitley's (2000) theory of degrees of mutual dependence and task uncertainty to explain the differences in the adoption and use of Academia.edu across the three disciplines. [ABSTRACT FROM AUTHOR]

Informed by a mature research base on what enhances the student experience, knowledge of the nature of the contemporary student and advances in technology and internet use, we can explore the potential to further evolve socialisation as part of the student experience. This paper reports on the evaluation and introduction of what has become known as 'online social networking' as one of the ways in which students can become 'socialised' within their university environment. The aim was to provide an educationally focused online social networking environment that is serious in its purpose and objectives, but which retains the user attractiveness of the major general purpose social networking systems. The range of technology options available is discussed and conclusions are drawn which indicate that a successful form of educational online social networking can be established with very simple technology. [ABSTRACT FROM AUTHOR]