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1
Jordan, Katy. "Academics’ online connections." Proceedings of the International Conference on Networked Learning 10 (May 9, 2016): 414–21. http://dx.doi.org/10.54337/nlc.v10.8900.
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Academic social networking sites (SNS), such as Academia.edu and ResearchGate, seek to bring the benefits of online social networking to academics' professional lives. Online academic social networking offers the potential to revolutionise academic publishing, foster novel collaborations, and empower academics to develop their professional identities online. However, the role that such sites play in relation to academic practice and other social media is not well understood at present. Arguably, the defining characteristic of academic social networking sites is the connections formed between profiles (in contrast to the traditional static academic homepage, for example). The social network of connections fostered by SNSs occupies an interesting space in relation to online identity, being both an attribute of an individual and shaped by the social context they are embedded within. As such, personal network structures may reflect an expression of identity (as "public displays of connection" (Donath & boyd, 2004) or "relational self portraits[s]" (Hogan & Wellman, 2014)), while social capital has been linked to network structures (Crossley et al., 2015). Network structure may therefore have implications for the types of roles that a network can play in professional life. What types of network structures are being fostered by academic SNS and how do they relate to academics' development of an online identity? This presentation will discuss findings from a project which has used a mixed-methods social network analysis approach to analyse academics' personal networks online. The personal networks of 55 academics (sampled from survey participants, to reflect a range of disciplines and job positions) on both one academic SNS (either Academia.edu or ResearchGate) and Twitter were collected and analysed. Differences in network structure emerged according to platform, with Twitter networks being larger and less dense, while academic SNS networks were smaller and more highly clustered. There were differences between academic SNS and Twitter in the brokerage positions occupied by the participant. The results are discussed in relation to other salient studies relating network structure in online social networks to social capital, and implications for academic practice. Future work, including co-interpretive interviews to explore the significance of network structures with participants, is introduced.
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Sivoronova, Jevgenija, Aleksejs Vorobjovs, and Vitālijs Raščevskis. "Academics’ Epistemological Attitudes towards Academic Social Networks and Social Media." Philosophies 9, no. 1 (2024): 18. http://dx.doi.org/10.3390/philosophies9010018.
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Academic social networks and social media have revolutionised the way individuals gather information and express themselves, particularly in academia, science, and research. Through the lens of academics, this study aims to investigate the epistemological and psychosocial aspects of these knowledge sources. The epistemological attitude model presented a framework to delve into and reflect upon the existence of knowledge sources, comprising subjective, interactional, and knowledge dimensions. One hundred and twenty-six university academics participated in this study, including lecturers and researchers from different higher education institutions in Latvia. The study employed two methods: the Epistemological Attitudes towards Sources of Knowledge Questionnaire and the Epistemological Attitudes towards Sources of Knowledge Semantic Questionnaire. The data analysis involved several procedures, including exploratory and confirmatory factor analysis, correlation analysis, and test statistics. By implementing these methods, the study gained valuable insights into the sources of knowledge, examining them from two perspectives. The first perspective brought attention to the differences in academics’ appraisals by discussing their understanding, approach, use, and valuations of these sources. By scrutinising the constructs of meanings, the second perspective sheds light on the anticipated knowledge which is deemed ideal, the concrete knowledge that is both social and objective, and the subjectively valuable nature of academic social networks and social media. The findings underscore the specialised knowledge and qualities that academics rely on for producing knowledge. In terms of epistemology, methodology, social science, and education, the study holds theoretical and practical implications, especially in comprehending knowledge and its sources.
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Andryani, Ria, Edi Surya Negara, Rezki Syaputra, and Deni Erlansyah. "Analysis of Academic Social Networks in Indonesia." Qubahan Academic Journal 3, no. 4 (2023): 409–21. http://dx.doi.org/10.58429/qaj.v3n4a289.
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Social network analysis to detect communities in social networks is a complex problem, this is due to differences in community definitions and the complexity of social networks. One of the social networks for researchers is the academic social network (ASN). We define the relationships between nodes in ASN into two forms, namely interconnection relationships and interaction relationships. Interconnection relationships are researchers' social relationships that are formed from similarities in discipline between researchers, while interaction relationships are researchers' social relationships that are formed through interactions carried out regarding joint article publications. This research aims to measure the social interactions and social interconnections of researchers in Indonesia using the social network analysis method. The ASN data used in this research comes from the academic social network Researchgate. This research produces information on the social networks of scientific groups in Indonesia and a framework for analyzing researchers' social networks using dual identification community mode which has been able to find and understand the structure of the research community based on records of interactions and interconnections with ASN with similarity values in both forms of network connections 85.9%.
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Cecchini, Mathilde, Maria Lehmann Nielsen, and Ea Høg Utoft. "Gender Dynamics in Academic Networks - a Narrative Review." Kvinder, Køn & Forskning, no. 1-2 (July 30, 2019): 86–98. http://dx.doi.org/10.7146/kkf.v28i1-2.116119.
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Progress towards gender balance among senior faculty in Danish academia remains slow. Although networks are widely recognized as key to career success, studies on the influence of gender on network dynamics and career advancement in academia are scarce. Until now, scholarship has engaged with the topic of gender and networks in organizations through two co-existing, while unrelated, streams of research, namely the social networks literature and the gendering networks literature. In this narrative review, we ask the following question: What characterizes the social networks literature and the gendering networks literature, and how can they inform each other and advance our understanding of gender dynamics in academic networks? We outline the main findings from the two literatures and discuss the potentials of combining different theoretical perspectives for understanding gender and networks in Danish academia. More specifically, we argue that the social networks literature maps the network structures of men and women, while the gendering networks literature takes us on a journey through these structures. This paper constitutes the first step of a research project entitled Gender and Networks in EarlyCareer Academic Advancement.
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Tauginienė, Loreta, and Rima Kalinauskaitė. "Participation of doctoral students in online social networks." Studies in Graduate and Postdoctoral Education 9, no. 2 (2018): 144–64. http://dx.doi.org/10.1108/sgpe-d-18-00002.
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Purpose This paper aims to examine the use of online social networks by doctoral students. Design/methodology/approach A quantitative online survey was conducted – 448 doctoral students from 15 universities and 11 research institutes in Lithuania were asked about their participation in both academic and non-academic online social networks. Findings The results show that despite efforts to link academics to society, doctoral students are not supported by universities/research institutes nor are doctoral students trained for this purpose, including regarding such threats as offensive posts. Additionally, more comprehensive information is disclosed in academic social networks, but these networks are less common and less frequently used. Research limitations/implications International doctoral students in Lithuania cover about 4.4 per cent of the total population of doctoral students. They were not invited to participate in the survey. Furthermore, doctoral students consider any online social network as their professional (academic) network, as was found from our results. This resulted in the confusion of our definition of academic online social networks. Practical implications Learning about the diverse online roles doctoral students may take could be facilitated were doctoral students to receive clear and consistent awareness-raising and develop self-awareness in the importance of the roles, the most central online social networks and potential threats, and related institutional support to address them. Originality/value This study provides results on how engagement of doctoral students in online social networks might affect their links with society and what academic institutions should promote in doctoral education.
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Fang, Jinjing, and Gavin T. L. Brown. "Academic Success at Social Costs: An Exploratory Study on Social Networks of Chinese Students under Academic Streaming." European Journal of Investigation in Health, Psychology and Education 14, no. 1 (2024): 164–80. http://dx.doi.org/10.3390/ejihpe14010011.
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In universities that require students to reside in dormitories, there are two types of social networks—study/classroom-based and social/dorm room-based. The academic streaming system may disrupt study/classroom connections, but its impact on students’ social networks is unknown. Using self-reported surveys, this study examines ego network measures of network sizes, turnover, multiplexity, and diversity among 382 students (44% female, 56% male). Surveys were administered before and after the university employed a first-semester grade-point average to demote or promote students into an honours college. Follow-up interviews were conducted with 11 honours students staying within their track and 11 students who were re-streamed to the non-honours track. Quantitative results showed that students in the non-honours college and who remained there had increasingly overlapping friendship circles between study and social environments, along with more diverse social connections, indicating stronger networks. In contrast, honours participants experienced fewer overlapping networks across domains and less dispersed social ties, especially after the academic replacement process. Qualitative results showed that the honours students faced a trade-off between academic success and social engagement in maintaining their elite status. Re-streamed students experienced otherness in social groups and decreased psychological wellbeing. This study contributes to the application of network analysis in education and provides insights into the unintended consequences of educational practice on students’ social networks.
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Boston, Ian. "Racing towards academic social networks." On the Horizon 17, no. 3 (2009): 218–25. http://dx.doi.org/10.1108/10748120910993240.
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Arif, Tasleem. "The Mathematics of Social Network Analysis: Metrics for Academic Social Networks." International Journal of Computer Applications Technology and Research 4, no. 12 (2015): 889–93. http://dx.doi.org/10.7753/ijcatr0412.1003.
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Verhees, Samira. "Social networks for academics." Journal of the Field Linguists Society 2024, no. 1 (2024): https://opling.github.io/journal/. https://doi.org/10.5281/zenodo.10611237.
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Academic social networks are convenient tools to enhance the visibility of your research and to stay updated on what colleagues are doing. This article provides an overview of the key features of the two main platforms (Academia.edu and ResearchGate), and discusses some of their drawbacks and possible alternatives.
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Goldstein, Scott. "Academic Social Networking Sites are Smaller, Denser Networks Conducive to Formal Identity Management, Whereas Academic Twitter is Larger, More Diffuse, and Affords More Space for Novel Connections." Evidence Based Library and Information Practice 15, no. 1 (2020): 226–28. http://dx.doi.org/10.18438/eblip29687.
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A Review of:
 Jordan, K. (2019). Separating and merging professional and personal selves online: The structure and processes that shape academics’ ego-networks on academic social networking sites and Twitter. Journal of the Association for Information Science and Technology, 70(8), 830-842. https://doi.org/10.1002/asi.24170
 Abstract
 Objective – To examine the structure of academics’ online social networks and how academics understand and interpret them.
 Design – Mixed methods consisting of network analysis and semi-structured interviews.
 Setting – Academics based in the United Kingdom.
 Subjects – 55 U.K.-based academics who use an academic social networking site and Twitter, of whom 18 were interviewed.
 Methods – For each subject, ego-networks were collected from Twitter and either ResearchGate or Academia.edu. Twitter data were collected primarily via the Twitter API, and the social networking site data were collected either manually or using a commercial web scraping program. Edge tables were created in Microsoft Excel spreadsheets and imported into Gephi for analysis and visualization. A purposive subsample of subjects was interviewed via Skype using a semi-structured format intended to illuminate further the network analysis findings. Transcripts were deductively coded using a grounded theory-based approach.
 Main Results – Network analysis replicated earlier findings in the literature. A large number of academics have relatively few connections to others in the network, while a small number have relatively many connections. In terms of reciprocity (the proportion of mutual ties or pairings out of all possible pairings that could exist in the network), arts and humanities disciplines were significantly more reciprocal. Communities (measured using the modularity algorithm, which looks at the density of links within and between different subnetworks) are more frequently defined by institutions and research interests on academic social networking sites and by research interests and personal interests on Twitter. The overall picture was reinforced by the qualitative analysis. According to interview participants, academic social networking sites reflect pre-existing professional relationships and do not foreground social interaction, serving instead as a kind of virtual CV. By contrast, Twitter is analogized to a conference coffee break, where users can form new connections.
 Conclusion – Academic social networking sites exhibit networks that are smaller, denser, more clustered around discrete modularity classes, and more reciprocal. Twitter networks are larger and more diffuse, which is more conducive to fostering novel connections. The author makes suggestions for how academic social networking sites could encourage network building and rethink how academic reputation is measured.
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Grant, Maria J., Robyn R. Lotto, and Ian D. Jones. "What we can learn from elite academic staff publication portfolios: a social network analysis." Aslib Journal of Information Management 72, no. 4 (2020): 605–24. http://dx.doi.org/10.1108/ajim-10-2019-0300.
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PurposeThe study aims to construct an understanding of professional academic writing network structures to inform organisational strategic investment in academic staff development.Design/methodology/approachLongitudinal social network analysis is used to examine the personal-networks evident in the publication portfolios of a purposive sample of four international academics across each quartile of the SCOPUS defined area of General Nursing's top 100 authors.FindingsTrends in the publication portfolios of elite academics across gender, sector and geographic location are presented. In the first years of successful writing for publication, authors collaborate within a single highly connected co-author network. This network will typically expand to include new co-authors, before additional separate co-author collaborations emerge (three- to four- years). Authors experience steady growth in co-author numbers four- to seven- years from first co-authored publication. After a period of rapid expansion, these collaborations coalesce into a smaller number of highly connected groups (eight- to ten- years). Most collaborations occur within the higher education sector and across multiple disciplines including medicine, social sciences and psychology. Male co-authors are disproportionately represented in what is a predominantly female profession.Practical implicationsThe development of extended co-author networks, locally, internationally and across the higher education sector, enable authors to attain the marker of achievement required by universities and government funding bodies, namely sustained output of academic publications. Identified trends support the inclusion of investment in academic time and resources in higher education institutions strategic and operational plans to enable academic staff to develop interdisciplinary professional networks. In focussing this investment on gender equality, female academics will experience parity of opportunity in achieving their organisational and personal goals relating to professional academic writing. Medium-term investment may be required before the impact of that investment becomes apparent.Originality/valueThis is the first example of social network analysis used to determine characteristics of professional academic writing portfolios over time. Findings inform the type and range of investment required to facilitate academic staff writing activities, specifically those publishing in the area of General Nursing.
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Arif, Tasleem. "Mining and Analyzing Academic Social Networks." International Journal of Computer Applications Technology and Research 4, no. 12 (2015): 878–83. http://dx.doi.org/10.7753/ijcatr0412.1001.
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Wankhade, Vaishali Yashwant, and Sapna Dattatre Kamble. "Social Networks Impact on Academic Libraries." International Journal of Research in Library Science 7, no. 4 (2021): 14. http://dx.doi.org/10.26761/ijrls.7.4.2021.1427.
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Chen, Po-Yen. "Academic social networks and collaboration patterns." Library Hi Tech 38, no. 2 (2019): 293–307. http://dx.doi.org/10.1108/lht-01-2019-0026.
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Purpose This study attempts to use a new source of data collection from open government data sets to identify potential academic social networks (ASNs) and defines their collaboration patterns. The purpose of this paper is to propose a direction that may advance our current understanding on how or why ASNs are formed or motivated and influence their research collaboration. Design/methodology/approach This study first reviews the open data sets in Taiwan, which is ranked as the first state in Global Open Data Index published by Open Knowledge Foundation to select the data sets that expose the government’s R&D activities. Then, based on the theory review of research collaboration, potential ASNs in those data sets are identified and are further generalized as various collaboration patterns. A research collaboration framework is used to present these patterns. Findings Project-based social networks, learning-based social networks and institution-based social networks are identified and linked to various collaboration patterns. Their collaboration mechanisms, e.g., team composition, motivation, relationship, measurement, and benefit-cost, are also discussed and compared. Originality/value In traditional, ASNs have usually been known as co-authorship networks or co-inventorship networks due to the limitation of data collection. This study first identifies some ASNs that may be formed before co-authorship networks or co-inventorship networks are formally built-up, and may influence the outcomes of research collaborations. These information allow researchers to deeply dive into the structure of ASNs and resolve collaboration mechanisms.
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Ovadia, Steven. "ResearchGate and Academia.edu: Academic Social Networks." Behavioral & Social Sciences Librarian 33, no. 3 (2014): 165–69. http://dx.doi.org/10.1080/01639269.2014.934093.
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Fernández-Pérez, Virginia, Patricia Esther Alonso-Galicia, María del Mar Fuentes-Fuentes, and Lazaro Rodriguez-Ariza. "Business social networks and academics' entrepreneurial intentions." Industrial Management & Data Systems 114, no. 2 (2014): 292–320. http://dx.doi.org/10.1108/imds-02-2013-0076.
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Purpose – This study analyses the role of social networks and their effects on academics' entrepreneurial intentions (AEI), from an academic cognitive perspective. Specifically, the paper investigates how business (distinguishing between industrial and financial links) and personal social networks, through opportunity-relevant information and support, could influence academics' intentions to start a business venture on the basis of their research knowledge. The paper examines the mediator roles of entrepreneurial attitudes (EA) and self-efficacy on opportunity recognition (SOR) as important psychological variables for academics. In the same context, the paper examines the mediator role of gender. Design/methodology/approach – The hypotheses were tested using structural equation modelling analysis, on a sample population of 500 Spanish academics engaged in commercially oriented fields of research. Findings – The results obtained highlight the positive roles played by business (industrial and financial) networks, both directly in promoting AEI, and indirectly via EA and SOR. The paper finds that male and female academics differ in their perceptions of support from business and financial networks and in their use of these resources in business start-up. Practical implications – An understanding of these issues offers opportunities to shape government interventions to assist academic entrepreneurs embarking on a business venture, or those already active in this respect, increasing their effectiveness in building, utilizing and enhancing the quality of networking activities. Originality/value – The paper explores business networking for academics as a factor promoting entrepreneurship. Furthermore, the paper considers an under-researched area that of female entrepreneurship in what is traditionally considered a male-dominated activity.
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Bibi, Fizza, Hikmat Khan, Tassawar Iqbal, Muhammad Farooq, Irfan Mehmood, and Yunyoung Nam. "Ranking Authors in an Academic Network Using Social Network Measures." Applied Sciences 8, no. 10 (2018): 1824. http://dx.doi.org/10.3390/app8101824.
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Online social networks are widely used platforms that enable people to connect with each other. These social media channels provide an active communication platform for people, and they have opened new venues of research for the academic world and business. One of these research areas is measuring the influential users in online social networks; and the same is true for academic networks where finding influential authors is an area of interest. In an academic network, citation count, h-index and their variations are used to find top authors. In this article, we propose the adoption of established social network measures, including centrality and prestige, in an academic network to compute the rank of authors. For the empirical analysis, the widely-used dataset of the Digital Bibliography and Library Project (DBLP) is exploited in this research, and the micro-level properties of the network formed in the DBLP co-authorship network are studied. Afterwards, the results are computed using social network measures and evaluated using the standard ranking performance evaluation measures, including Kendall correlation, Overlapping Similarlity (OSim) and Spearman rank-order correlation. The results reveal that the centrality measures are significantly correlated with the citation count and h-index. Consequently, social network measures have potential to be used in an academic network to rank the authors.
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Gaughan, Monica, Julia Melkers, and Eric Welch. "Differential Social Network Effects on Scholarly Productivity." Science, Technology, & Human Values 43, no. 3 (2017): 570–99. http://dx.doi.org/10.1177/0162243917735900.
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Academic productivity is realized through resources obtained from professional networks in which scientists are embedded. Using a national survey of academic faculty in Science, Technology, Engineering, and Mathematics (STEM) fields across multiple institution types, we examine how the structure of professional networks affects scholarly productivity and how those effects may differ by race, ethnicity, and gender. We find that network size masks important differences in composition. Using negative binomial regression, we find that both the size and composition of professional networks affect scientific productivity, but bigger is not always better. We find that instrumental networks increase scholarly productivity, while advice networks reduce it. There are important interactive effects that are masked by modeling only direct effects. We find that white men are especially advantaged by instrumental networks, and women are especially advantaged by advice networks.
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Stadtfeld, Christoph, András Vörös, Timon Elmer, Zsófia Boda, and Isabel J. Raabe. "Integration in emerging social networks explains academic failure and success." Proceedings of the National Academy of Sciences 116, no. 3 (2018): 792–97. http://dx.doi.org/10.1073/pnas.1811388115.
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Academic success of students has been explained with a variety of individual and socioeconomic factors. Social networks that informally emerge within student communities can have an additional effect on their achievement. However, this effect of social ties is difficult to measure and quantify, because social networks are multidimensional and dynamically evolving within the educational context. We repeatedly surveyed a cohort of 226 engineering undergraduates between their first day at university and a crucial examination at the end of the academic year. We investigate how social networks emerge between previously unacquainted students and how integration in these networks explains academic success. Our study measures multiple important dimensions of social ties between students: their positive interactions, friendships, and studying relations. By using statistical models for dynamic network data, we are able to investigate the processes of social network formation in the cohort. We find that friendship ties informally evolve into studying relationships over the academic year. This process is crucial, as studying together with others, in turn, has a strong impact on students’ success at the examination. The results are robust to individual differences in socioeconomic background factors and to various indirect measures of cognitive abilities, such as prior academic achievement and being perceived as smart by other students. The findings underline the importance of understanding social network dynamics in educational settings. They call for the creation of university environments promoting the development of positive relationships in pursuit of academic success.
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Maydangalieva, Zhumagul Aldiyarovna, Svetlana Ermekbaevna Doszhanova, Nurgul Moldabaevna Abisheva, and G. Nazarova. "SOCIAL NETWORKS AS REFLECTION OF ACADEMIC PERFORMANCE." BULLETIN 6, no. 376 (2018): 95–103. http://dx.doi.org/10.32014/2018.2518-1467.32.
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Hoang, Dinh Tuyen, Ngoc Thanh Nguyen, Van Cuong Tran, and Dosam Hwang. "Research collaboration model in academic social networks." Enterprise Information Systems 13, no. 7-8 (2018): 1023–45. http://dx.doi.org/10.1080/17517575.2018.1556812.
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Suleiman, Muhammad Muhammad, and Shitu Sani. "Social networks as integral of ICT: a predictor of academic procrastination." Kampala International University Interdisciplinary Journal of Humanities and Social Sciences 1, no. 2 (2020): 229–41. http://dx.doi.org/10.59568/kijhus-2020-1-2-16.
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Internet applications simultaneously are a driving force to the cultural dividend of social networks among the students of higher education. Social networks as an interactive form of networks that allow the user to with and publish to each other, generally utilizing the internet provide a ground for multiple purposes activities ranging from pleasure, business, official and academic purposes. This paper intends to discuss the other side of social networks as it influences the prediction of academic procrastination among the students of higher education. Students' tendency for irrational task delay (i.e. procrastination) may be particularly lying face down to use Internet applications simultaneously to other tasks (e.g., during homework) and in an inadequately controlled approach. It is also a review of some literature related to the topic under discussion. Issues relate to the use of social networks for other activities in the name of academics and turn to academic procrastination is common among the students of higher education. Students are more pleasure seeking than academic participation unless otherwise. Therefore, the paper suggests some techniques that low down the social networks as a predictor of academic procrastination.
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Fuentes Cancell, Dieter Reynaldo, Odiel Estrada Molina, and Nilda Delgado Yanes. "Las redes sociales digitales: una valoración socioeducativa. Revisión sistemática." Revista Fuentes 1, no. 23 (2021): 41–52. http://dx.doi.org/10.12795/revistafuentes.2021.v23.i1.11947.
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The future and already current industrial revolution 4.0 demand the introduction of a digital transformation in the higher education contributing to the formation of competent professionals, for which, they are evidenced in the pedagogies and emergent technologies, an increase of didactic experiences in the use of the digital social networks. In this research a systematic review to identify current trends in the use of online social networks for educational purposes are performed. PRISMA protocol was used and analyzed 79 studies present in the database Scopus. In the systematic review, the following questions are answered: What types of designs predominate in the scientific literature? What is the dependentindependent pairs of variables? And What are the current trends in the use of digital social networks for educational purposes? As a result of this research, Facebook is reaffirmed as the social network most used by educators and the need for the integrated and varied use of these networks. It concludes with the defense of the following trends: university institutional communication policies from the curricular levels; the development of creativity, cultural convergence and media diversification; educational innovation; media culture and academic digital identity
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Gao, Ruyi. "Research on the Impact of Peer Social Networks on Students Physical and Mental Development and Campus Happiness." Lecture Notes in Education Psychology and Public Media 25, no. 1 (2023): 128–33. http://dx.doi.org/10.54254/2753-7048/25/20230642.
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This study addresses the influence of social networks on university students academic performance and psychological well-being. With over forty million students engaged in higher education in China, enhancing their educational experience and mental health amidst limited resources has become crucial. Existing research often focuses on educational structures and learning experiences, neglecting campus environment-related factors. Therefore, this study emphasizes the role of social networks in shaping outcomes. Drawing from historical literature, social network analysiss efficacy in addressing societal concerns is established. Studies reveal that students with more reciprocal connections often exhibit better academic performance. This research amalgamates empirical inquiries, examining network data, academic achievements, and well-being indicators. Findings underscore social networks potential to influence academic and psychological dimensions, offering implications for universities and students.
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Al-Muomen, Nujoud, Abdus Sattar Chaudhry, and Oroba Al-Othinah. "Perceptions regarding academic social networks for scholarly communications." Global Knowledge, Memory and Communication 69, no. 8/9 (2020): 597–611. http://dx.doi.org/10.1108/gkmc-01-2020-0007.
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Purpose This study aims to investigate the perceptions of academics regarding the use and usefulness of academic social networks (ASNs) in the scholarly communication practices of faculty members in Kuwaiti Universities. Design/methodology/approach The study was conducted through a survey. In total, 100 faculty members from the disciplines of business administration, humanities and social sciences from three universities in Kuwait filled in an online questionnaire. The statistical feature of the Web-based tool was used for data analysis. Findings The results show that most faculty members are aware of the importance of ASNs. They perceive that these networks are useful, as more publications have become available, it has become easier for scholars to connect with colleagues who share similar research interests. Research limitations/implications The study is descriptive and restricted to a specific country (Kuwait). It also only covered faculty members from three academic disciplines. Furthermore, the use of a questionnaire, while appropriate for descriptive research, restricted us from conducting probing designed to gain deeper insights regarding participants’ motivations and explanations for not realizing the potential of these networks. Practical implications Future research should expand the scope of this study to cover faculty members from other disciplines (e.g. science, engineering and medicine), while also including more universities from other countries in the Arabian Gulf region. Future research should also examine how academics’ information-finding practices are changing as a result of the availability of information sources through ASNs. Originality/value No similar study has been conducted previously in Kuwait. This study provided useful information regarding the use and perceptions of ASNs in the context of faculty members of Kuwaiti universities. This information is of interest to scholars, information providers and those who design such networks.
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Hadgu, Asmelash Teka, and Jayanth Kumar Reddy Gundam. "Learn2Link: Linking the Social and Academic Profiles of Researchers." Proceedings of the International AAAI Conference on Web and Social Media 14 (May 26, 2020): 240–49. http://dx.doi.org/10.1609/icwsm.v14i1.7295.
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People have presence across different information networks on the social web. The problem of user identity linking, is the task of establishing a connection between accounts of the same user across different networks. Solving this problem is useful for: personalized recommendations, cross platform data enrichment and verifying online information among others. In this paper, we propose a deep learning based approach that jointly models heterogeneous data: text content, network structure as well as profile names and images, in order to solve the user identity linking problem. We perform experiments on a real world problem of connecting the social profile (Twitter) and academic profile (DBLP) of researchers. Experimental results show that our joint model achieves a 97% F1 score outperforming state-of-the-art results that consider profile, content or network features only.
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Nurcahyo, Bagus. "IS THERE ANY IMPACT OF SOCIAL MEDIA ON ACADEMIC PERFORMANCE? (An Empirical Study From College Student In Jakarta)." JURNAL NUSANTARA APLIKASI MANAJEMEN BISNIS 2, no. 2 (2017): 101. http://dx.doi.org/10.29407/nusamba.v2i2.849.
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This study aimed to examine empirically the social network activities that affect academic performance. Obtain sample data using questionnaires and obtain data from top 10 universities in Webometrics and total 75 respondents. This study examined the utilization period of social networks, social network usage motivation, academic data and activities respondents perceived influence on academic performance. Using multiple regression techniques, the study found that social network activity does not negatively impact on academic performance.
 
 Keywords: social network, Facebook, Twitter, Academic Performance, GPA
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Lytras, Miltiadis, Hassan Mathkour, Hassan Abdalla, Cornelio Yanez-Marquez, and de Pablos Patricia Ordóñez. "The Social Media in Academia and EducationResearch R-evolutions and a Paradox: Advanced Next Generation Social Learning Innovation." JUCS - Journal of Universal Computer Science 20, no. (15) (2014): 1987–94. https://doi.org/10.3217/jucs-020-15.
Texte intégralRésumé :
This editorial presents an evolutionary model for the adoption of Social Media and Social Networks in Academia. It seems that the rapid development of technological infrastructures in the context of social networks had to face inflexible structures in Academic Institutions in the same moment where students in a massive way adopt social networks for different purposes than learning. The evolution of social media research in the last five years is significant. A number of issues related to the formation, development and adoption of social networks in different domains have been investigated promoting the scientific debate. In this special issue the emphasis is on the adoption of social networks in learning and knowledge management domains in academic settings. The bold contribution of our meta-analysis in this guest editorial is the specification of the open research issues that can initiate further research. To our understanding an evolutionary model is confirmed and defines a context of exploitation for the contribution of social networks research towards more effective next generation learning systems in academia. Beyond the fashion of use of social media for learning purposes, there is a multidisciplinary orientation towards flexible personalized learning contexts. Furthermore a number of enablers are presented. This editorial can serve as a position document for scientific debate fostering international collaboration and empirical research in the various aspects of the well-defined agenda. It can also serve as a reference edition for researchers interested in the adoption of Social Networks, in the Academia.
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Vermond, Debbie, Esther de Groot, Valerie A. Sills, et al. "The evolution and co-evolution of a primary care cancer research network: From academic social connection to research collaboration." PLOS ONE 17, no. 7 (2022): e0272255. http://dx.doi.org/10.1371/journal.pone.0272255.
Texte intégralRésumé :
Academic networks are expected to enhance scientific collaboration and thereby increase research outputs. However, little is known about whether and how the initial steps of getting to know other researchers translates into effective collaborations. In this paper, we investigate the evolution and co-evolution of an academic social network and a collaborative research network (using co-authorship as a proxy measure of the latter), and simultaneously examine the effect of individual researcher characteristics (e.g. gender, seniority or workplace) on their evolving relationships. We used longitudinal data from an international network in primary care cancer research: the CanTest Collaborative (CanTest). Surveys were distributed amongst CanTest researchers to map who knows who (the ‘academic social network’). Co-authorship relations were derived from Scopus (the ‘collaborative network’). Stochastic actor-oriented models were employed to investigate the evolution and co-evolution of both networks. Visualizing the development of the CanTest network revealed that researchers within CanTest get to know each other quickly and also start collaborating over time (evolution of the academic social network and collaborative network respectively). Results point to a stable and solid academic social network that is particularly encouraging towards more junior researchers; yet differing for male and female researchers (the effect of individual researcher characteristics). Moreover, although the academic social network and the research collaborations do not grow at the same pace, the benefit of creating academic social relationships to stimulate effective research collaboration is clearly demonstrated (co-evolution of both networks).
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Sánchez-Teba, Eva M., Mercedes Rodríguez-Fernández, and Ana I. Gaspar-González. "Social Networks and Open Innovation: Business Academic Productivity." Journal of Open Innovation: Technology, Market, and Complexity 7, no. 2 (2021): 158. http://dx.doi.org/10.3390/joitmc7020158.
Texte intégralRésumé :
Is there any type of relationship between the academic productivity of business researchers and their social networking activity? What does this mean in terms of open innovation? With these objectives, in this paper we have focused on the Technology Acceptance Model and the concept of performativity, filling the gap that exists in the current scientific literature. At the empirical level, we carried out a review of 211 articles from the Web of Science (SSCI), obtaining a total set of 12,939 data points. Our statistical model has showed a clear symbiotic relationship between productivity in Google Scholar and presence in ResearchGate. Furthermore, researchers with a greater presence on LinkedIn or Twitter have low Google Scholar or Web of Science h-indices. We concluded that there is currently a dissociation between academic and professional online networks, something that does not help the applicability of research in business and society, the enduring aim of any search for knowledge. Information Science can play an important role in helping to bridge the gap between academia and the real world. Furthermore, in order to contribute to enhancing the role of universities in open innovation practices, it is essential to design and implement new tools such as online communities that stimulate interaction and facilitate network effects.
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Shin, Huiyoung. "Social contagion of academic behavior: Comparing social networks of close friends and admired peers." PLOS ONE 17, no. 3 (2022): e0265385. http://dx.doi.org/10.1371/journal.pone.0265385.
Texte intégralRésumé :
Peer relations become significant socializing agents for diverse behaviors during adolescence. This study investigated relationship selection and social influence of early adolescents’ close friends and admired peers with regard to academic behavioral engagement. A stochastic actor-based model of social network analysis was used to examine classroom social networks across 2 waves (Mage = 11.46; N = 542) based on peer nominations. Adolescents were asked to nominate their “close friends they hang around with and talk to the most” and peers that they “admire, respect, and want to be like” Results indicated that adolescents who were similar in academic engagement more often became friends. Also, close friends’ and admired peers’ academic engagement contributed to adolescents’ own academic engagement over time. The results suggest that both close friends and admired peers are important channels for social contagion of academic behavior and that examining social relations beyond friends are important for advancing our understanding of peer social influence during adolescence.
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Yeşilbaş Özenç, Yasemin, and Bertan Akyol. "Social Network and Organizational Power Distance: A Mixed Method Research on Academic Staff." Journal of Higher Education and Science 14, no. 2 (2024): 265–81. http://dx.doi.org/10.5961/higheredusci.1366785.
Texte intégralRésumé :
In the study, which was carried out to compare the perception of organizational power distance of the academic staff working at the university with the social networks they established with their colleagues at the university, the quantitative and qualitative data collection and analysis processes were carried out simultaneously using the Convergent Parallel Design, one of the mixed methods research designs, and the results of the data analysis were integrated. This research compares the organizational power distance perceptions of the faculty members working at A University, a public university in Turkey, with the social networks they have established with their colleagues at the university. In the quantitative dimension of the research carried out with the mixed method, the research population consists of 1848 academic staff working at A University, one of the public universities in Turkey, in the 2020-2021 academic year. The research sample consists of 319 academic staff. 385 academic staff from 30 academic units, 14 faculties, and 16 colleges/vocational schools, were included in the research. In the qualitative dimension of the research, 27 of 34 academic staff working in the C Department of the B Faculty of the A University were included in the study group. Convergent Parallel Design was used in the research; within this context, the quantitative and qualitative data collection and analysis processes were carried out simultaneously and the data analysis results were integrated. The quantitative data were analyzed with the SPSS 21 program, the participants' views on organizational power distance were analyzed with the MAXQDA 2022 program, and social network analysis data were analyzed with the UCINET 6.0 program. According to the research findings' conclusion, the academic staff's general social network tendencies in the quantitative dimension were high, and the participants had the highest perception of "liking to connect." It was determined that the academic staff's general organizational power distance perceptions were at a moderate level, and the participants had the highest perception of "acquiescence of power." Another conclusion was that the social network tendencies of academic staff did not differ according to the academic title variable. However, the organizational power distance differed significantly in favor of research assistants. It was revealed that there was no statistically significant relationship between the general social network tendencies of the academic staff and their perception of organizational power distance. In the qualitative dimension of the study, it was observed that the participants expressed their opinions on organizational power distance mostly in terms of accepting power and least in terms of consenting to power. Social network analysis revealed that the professional network had a denser structure than the friendship network, but the friendship network had more structured and stronger ties. In social networks, professors and research assistants were found to be at the center of the network. The study observed that the results of quantitative and qualitative data analysis confirmed each other at many points. This study is expected to contribute to the literature, policymakers in higher education management, university senior management, academics, and researchers.
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Del Valle, Marc Esteve, and Silvia Donker. "Special Theme: Homophily in Social Networks." Connections 44, no. 1 (2024): 2–3. https://doi.org/10.21307/connections-2019.039.
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Abstract Over the last thirty years, in parallel with the global uptake of the world wide web, social network analysis (SNA) has become a significant analytical approach within several disciplines and it currently holds a prominent position in academic discussions across a diverse range of topics. This special theme of Connections, the journal of the International Network for Social Network Analysis, adds to the rapidly growing body of network research with a focus on exploring the principle of homophily in social networks. It presents 5 studies from a selected number of participants to the symposium “Similarity, Selection and Influence: A Cross-Disciplinary Symposium on Homophily in Social Networks” (7–8 July, 2022, Groningen, the Netherlands). Taken together, the special theme provides an interdisciplinary understanding of homophily in social networks and outlines avenues for future research to keep investigating the subject.
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Cenková, Renáta, and William Steingartner. "Use of Internet Social Networks in Academic Environment." Journal of information and organizational sciences 44, no. 2 (2020): 275–95. http://dx.doi.org/10.31341/jios.44.2.5.
Texte intégralRésumé :
Numerous national and private Slovak universities and colleges are currently confronted with a state, where the offer of study programmes exceeds its demand - students’ interests. This paper describes reasons for this situation but mainly it points out the fact that the advent of information and communication technologies significantly intervened in different areas of life and all types of communication. The implementation of some tools of internet social networks in the academic environment is, therefore, essential. In addition to the theoretical background, the paper also includes case study related to the creation of a new Facebook profile #MaŠtu, setting up specific online marketing key performance indicators (KPI) and monitoring them using both Facebook analytics metrics and the social networking tool for administration, ZoomSphere.
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K, Sobha Rani, Raju KVSVN, and V. Valli Kumari. "Application of Clustering to Analyze Academic Social Networks." International journal of Web & Semantic Technology 4, no. 2 (2013): 9–20. http://dx.doi.org/10.5121/ijwest.2013.4202.
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Amjad, Tehmina, Ali Daud, and Naif Radi Aljohani. "Ranking authors in academic social networks: a survey." Library Hi Tech 36, no. 1 (2018): 97–128. http://dx.doi.org/10.1108/lht-05-2017-0090.
Texte intégralRésumé :
Purpose This study reviews the methods found in the literature for the ranking of authors, identifies the pros and cons of these methods, discusses and compares these methods. The purpose of this paper is to study is to find the challenges and future directions of ranking of academic objects, especially authors, for future researchers. Design/methodology/approach This study reviews the methods found in the literature for the ranking of authors, classifies them into subcategories by studying and analyzing their way of achieving the objectives, discusses and compares them. The data sets used in the literature and the evaluation measures applicable in the domain are also presented. Findings The survey identifies the challenges involved in the field of ranking of authors and future directions. Originality/value To the best of the knowledge, this is the first survey that studies the author ranking problem in detail and classifies them according to their key functionalities, features and way of achieving the objective according to the requirement of the problem.
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Wan, Huaiyu, Yutao Zhang, Jing Zhang, and Jie Tang. "AMiner: Search and Mining of Academic Social Networks." Data Intelligence 1, no. 1 (2019): 58–76. http://dx.doi.org/10.1162/dint_a_00006.
Texte intégralRésumé :
AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations. The system is subsequently able to extract researchers’ profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation. Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise search. In addition, AMiner offers a set of researcher-centered functions, including social influence analysis, relationship mining, collaboration recommendation, similarity analysis, and community evolution. The system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions.
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Kong, Xiangjie, Yajie Shi, Shuo Yu, Jiaying Liu, and Feng Xia. "Academic social networks: Modeling, analysis, mining and applications." Journal of Network and Computer Applications 132 (April 2019): 86–103. http://dx.doi.org/10.1016/j.jnca.2019.01.029.
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Weintraub, Arlene. "Social networks attempt to spark academic–industry collaborations." Nature Biotechnology 30, no. 10 (2012): 901–2. http://dx.doi.org/10.1038/nbt1012-901.
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Gómez-Aguilar, Marisol, Sergio Roses-Campos, and Pedro Farias-Batlle. "The Academic Use of Social Networks among University Students." Comunicar 19, no. 38 (2012): 131–38. http://dx.doi.org/10.3916/c38-2012-03-04.
Texte intégralRésumé :
This paper examines the academic use made of the social networks by university students through a survey conducted among a representative sample of students at Universidad de Málaga (Spain) (n=938) and two discussion groups. Given that network consumption has profoundly penetrated the daily routines of the students, the vast communication possibilities of these channels could be considered for educational use in the future despite a predominance of entertainment-related use. We discuss the most suitable networks for academic use, which type of activities may be most widely accepted among the students and which social networking tools could be most useful for academic purposes. The results indicate that consumption of social networks in the student population surveyed is very high. In addition, the students show a favourable attitude to lecturers using social networks as an academic resource. However, the frequency of use of such networks for academic activities was rather low and, on average, the most frequently used academic activities are those initiated by the students themselves, such as answering queries among peers or doing coursework. The perceived low academic support on social networks may mean that lecturers take only limited advantage of their potential. El uso académico que hacen los universitarios de las redes sociales es el estudio que se presenta a partir de una encuesta administrada a una muestra representativa de estudiantes de la Universidad de Málaga (n=938) y dos grupos de discusión. Dado que el consumo de redes se ha implantado profundamente en las rutinas diarias de los estudiantes, las vastas posibilidades comunicativas de estos canales podrían considerarse para sacar provecho educativo en el futuro, a pesar del predominio del uso dirigido al entretenimiento. Se discuten cuáles son las redes más adecuadas para su uso académico, qué tipo de actividades pueden tener mejor acogida entre los estudiantes y qué herramientas de las redes sociales podrían ser más útiles para propósitos académicos. Los resultados indican que el consumo de redes sociales de la población estudiada es muy alto. Así mismo, los estudiantes presentan una actitud favorable a que los docentes utilicen las redes como recurso educativo. Sin embargo, la frecuencia con la que los estudiantes dan un uso académico a las redes es más bien escasa y, en promedio, las actividades académicas con frecuencia de uso más elevada son aquellas que parten de la iniciativa de los propios estudiantes, como la solución de dudas inter pares o la realización de trabajos de clase. Del escaso apoyo académico percibido en las redes por los estudiantes, se deduce un limitado aprovechamiento por parte de los docentes.
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Rimpelä, Arja, Jaana M. Kinnunen, Pirjo Lindfors, et al. "Academic Well-Being and Structural Characteristics of Peer Networks in School." International Journal of Environmental Research and Public Health 17, no. 8 (2020): 2848. http://dx.doi.org/10.3390/ijerph17082848.
Texte intégralRésumé :
Peer networks at school and students’ position in these networks can influence their academic well-being. We study here individual students’ network position (isolation, popularity, social activity) and peer network structures at the school level (centralization, density, clustering, school connectedness) and their relations to students’ academic well-being (school burnout, SB; schoolwork engagement, SE). Classroom surveys for 14–16-year-olds (N = 11,015) were conducted in six European cities (SILNE survey). Students were asked to nominate up to five schoolmates with whom they preferred to do schoolwork. SB and SE correlated negatively (−0.32; p < 0.0001). Students had on average 3.4 incoming (popularity; range 0–5) and 3.4 outgoing (social activity; 0–5) social ties. Percentage of isolated students was 1.4. Students’ network position was associated weakly with academic well-being—popular students had less SB and higher SE, and socially active students had higher SE. School-level peer networks showed high clustering and school connectedness, but low density and low centralization. Clustering was associated with higher SB. Low centralization and high school connectedness protected from SB. Dense networks supported SE as did high average school connectedness. Correlations between these network indicators and academic well-being were, however, low. Our study showed that both students’ network position and network characteristics at the school level can influence adolescents’ academic well-being.
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Guo, Yiyang, and Zheyu Zhou. "SSRES: A Student Academic Paper Social Recommendation Model Based on a Heterogeneous Graph Approach." Mathematics 12, no. 11 (2024): 1667. http://dx.doi.org/10.3390/math12111667.
Texte intégralRésumé :
In an era overwhelmed by academic big data, students grapple with identifying academic papers that resonate with their learning objectives and research interests, due to the sheer volume and complexity of available information. This study addresses the challenge by proposing a novel academic paper recommendation system designed to enhance personalized learning through the nuanced understanding of academic social networks. Utilizing the theory of social homogeneity, the research first constructs a sophisticated academic social network, capturing high-order social relationships, such as co-authorship and advisor–advisee connections, through hypergraph modeling and advanced network representation learning techniques. The methodology encompasses the development and integration of a hypergraph convolutional neural network and a contrastive learning framework to accurately model and recommend academic papers, focusing on aligning with students’ unique preferences and reducing reliance on sparse interaction data. The findings, validated across multiple real-world datasets, demonstrate a significant improvement in recommendation accuracy, particularly in addressing the cold-start problem and effectively mapping advisor–advisee relationships. The study concludes that leveraging complex academic social networks can substantially enhance the personalization and precision of academic paper recommendations, offering a promising avenue for addressing the challenges of academic information overload and fostering more effective personalized learning environments.
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Smith, Rachel A., Michael G. Brown, Kevin A. Grady, Stephanie Sowl, and Jessica M. Schulz. "Patterns of Undergraduate Student Interpersonal Interaction Network Change During the COVID-19 Pandemic." AERA Open 8 (January 2022): 233285842110731. http://dx.doi.org/10.1177/23328584211073160.
Texte intégralRésumé :
In spring 2020, many U.S. colleges and universities rapidly shifted to online instruction and implemented social distancing policies to respond to the COVID-19 pandemic. Students experienced unprecedented disruption of their interpersonal academic and social networks due to the loss of physical proximity. We used egocentric network analysis and latent profile analysis with survey data from April 2020 and conducted follow-up interviews in September 2020 to examine some of the pandemic’s immediate effects on student interpersonal network change. We found the disappearance of interpersonal network patterns featuring coworkers and academic ties, as well as reductions in students’ overall number of connections and the role diversity of their networks. Results suggest potential ongoing reduction of peer academic relationships, implying that institutional personnel may need to pay particular attention to academic connections in online spaces and to regenerating students’ academic networks when on-campus physical spaces may again be used to support learning.
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Ali, Akbar Ebrahimi, and Azar Fatemeh. "The Effect of Excessive Use of Virtual Social Networks on the Academic Performance of Bamyan University Students: The Mediating Role of Qualityof Sleep." International Journal of Social Science And Human Research 04, no. 04 (2021): 723–29. https://doi.org/10.47191/ijsshr/v4-i4-21.
Texte intégralRésumé :
Background: The social networks are used today as one of the important tools in establishing communication between people. In addition to the advantages, it can also have several disadvantages and problems, the negative effects of which can be seen on the academic performance of students. Objective: This study was designed to investigate the role of excessive use of virtual social networks on the academic performance of Bamyan University students with a mediating role of quality of sleep. Methodology: The present study has a descriptive-correlational design. A total of 180 Bamyan University students (90 male and 90 female) were selected by convenience sampling method and responded to the Pittsburgh Sleep Quality Questionnaire (Buysee et al., 1989), Yang Internet and Social Network Addiction Questionnaire, Demographic Questions, and GPA of last semester. Data were analyzed using Pearson correlation test and hierarchical regression analysis by means of SPSS-24. Results: The results showed that the excessive use of social networks had a significant negative correlation with academic performance and predicts it inversely (T = -9.338, ß = - 730) and There is also a significant relationship between excessive use of social networks and quality of sleep (T = 15.726, ß = .763). There was a significant relationship between social and sleep quality (T = 15.726, ß = .763). But sleep quality could not play a mediating role between excessive use of social networks and students' academic achievement and showed that this relationship is not significant (T = -. 174, ß = -. 014). Conclusion: Excessive use of social networks has negative effects on students' academic achievement and quality of sleep. For this purpose, it is necessary to manage the use of social networks for optimal use in order to achieve high academic achievement and good quality of sleep
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Ph.D., Irma Leticia Chávez Márquez *. "USE OF SOCIAL NETWORKS AND ACADEMIC PERFORMANCE IN EXACT SCIENCES IN UNIVERSITY STUDENTS." INTERNATIONAL JOURNAL OF RESEARCH SCIENCE & MANAGEMENT 4, no. 10 (2017): 67–74. https://doi.org/10.5281/zenodo.1037669.
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The increase use of social networks gives way to new didactic strategies in university students. The objective of the research was to analyze the relationship between the use of the social network Facebook and academic performance in the subject Statistics in university students. The way the research was descriptive and correlational between the variables (use of social networks and academic performance). The research focus was mixed, applied type, the design was quasi-experimental. The research was carried out in the Facultad de Contaduría y Administración of the Universidad Autónoma de Chihuahua. The unit of analysis were students enrolled in the subject of Statistics. The sample size was 174 students. It was validated with a Cronbach alpha coefficient of 0.847. The main results indicate when we used the social network Facebook, we observed a better academic performance. As we had a greater participation in the social network Facebook, the final semester grade was best.It is necessary to continue with lines of research to follow up on the topic dealt with, both in the results obtained in the long term with the formal implementation of the use of social networks, and in the possible problems generated by its use.
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Soodan, Vishal, Avinash Rana, Anurag Jain, and Deeksha Sharma. "AI Chatbot Adoption in Academia: Task Fit, Usefulness and Collegial Ties." Journal of Information Technology Education: Innovations in Practice 23 (2024): 001. http://dx.doi.org/10.28945/5260.
Texte intégralRésumé :
Aim/Purpose: This mixed-methods study aims to examine factors influencing academicians’ intentions to continue using AI-based chatbots by integrating the Task-Technology Fit (TTF) model and social network characteristics. Background: AI-powered chatbots are gaining popularity across industries, including academia. However, empirical research on academicians’ adoption behavior is limited. This study proposes an integrated model incorporating TTF factors and social network characteristics like density, homophily, and connectedness to understand academics’ continuance intentions. Methodology: A qualitative study involving 31 interviews of academics from India examined attitudes and the potential role of social network characteristics like density, homophily, and connectedness in adoption. Results showed positive sentiment towards chatbots and themes on how peer groups accelerate diffusion. In the second phase, a survey of 448 faculty members from prominent Indian universities was conducted to test the proposed research model. Contribution: The study proposes and validates an integrated model of TTF and social network factors that influence academics’ continued usage intentions toward AI chatbots. It highlights the nuanced role of peer networks in shaping adoption. Findings: Task and technology characteristics positively affected academics’ intentions to continue AI chatbot usage. Among network factors, density showed the strongest effect on TTF and perceived usefulness, while homophily and connectedness had partial effects. The study provides insights into designing appropriate AI tools for the academic context. Recommendations for Practitioners: AI chatbot designers should focus on aligning features to academics’ task needs and preferences. Compatibility with academic work culture is critical. Given peer network influences, training and demonstrations to user groups can enhance adoption. Platforms should have capabilities for collaborative use. Targeted messaging customized to disciplines can resonate better with academic subgroups. Multidisciplinary influencers should be engaged. Concerns like plagiarism risks, privacy, and job impacts should be transparently addressed. Recommendation for Researchers: More studies are needed across academic subfields to understand nuanced requirements and barriers. Further studies are recommended to investigate differences across disciplines and demographics, relative effects of specific network factors like size, proximity, and frequency of interaction, the role of academic leadership and institutional policies in enabling chatbot adoption, and how AI training biases impact usefulness perceptions and ethical issues. Impact on Society: Increased productivity in academia through the appropriate and ethical use of AI can enhance quality, access, and equity in education. AI can assist in mundane tasks, freeing academics’ time for higher-order objectives like critical thinking development. Responsible AI design and policies considering socio-cultural aspects will benefit sustainable growth. With careful implementation, it can make positive impacts on student engagement, learning support, and research efficiency. Future Research: Conduct longitudinal studies to examine the long-term impacts of AI chatbot usage in academia. Track usage behaviors over time as familiarity develops. Investigate differences across academic disciplines and roles. Requirements may vary for humanities versus STEM faculty or undergraduate versus graduate students. Assess user trust in AI and how it evolves with repeated usage, and examine trust-building strategies. Develop frameworks to assess pedagogical effectiveness and ethical risks of conversational agents in academic contexts.
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Moglen, Daniel. "International Graduate Students: Social Networks and Language Use." Journal of International Students 7, no. 1 (2017): 22–37. http://dx.doi.org/10.32674/jis.v7i1.243.
Texte intégralRésumé :
The campus climate for international graduate students (IGSs) has been gaining attention in recent years as the number of IGSs in the United States continues to rise. IGSs bring diversity to the campus community and enrich the academic community, but also come to the table with distinct needs, concerns, and experiences. The current study is primarily concerned with how early social and academic experiences affect English learning and academic success. Social networks outside of the student’s cultural background may be difficult to develop, and, therefore, it is not uncommon to see students gravitate towards others who share their cultural and language background.
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González-Gamboa, Vladimir, and Jennyfer León-Mena. "Educational Networks as Evidence of Students' Interactions in Mathematical Learning." Advances in Educational Research and Evaluation 5, no. 1 (2025): 278–92. https://doi.org/10.25082/aere.2024.01.004.
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This study explores the relationship between academic performance and social network structures among tenth-grade students in Costa Rican high schools. It aims to assess how interactions within and outside the classroom correlate with mathematics grades. Data were collected from 826 students across 35 schools, and social network analysis was conducted using various network statistics. Results indicate that classroom networks, marked by higher cohesion and density, exhibited a positive but statistically non-significant correlation with academic performance, whereas outside networks showed lower cohesion and negative correlations with grades. These findings underscore the potential benefits of fostering collaborative classroom interactions to improve learning outcomes. Future research should focus on teacher-guided group dynamics and external factors influencing outside networks to gain deeper insights into their impact on academic achievement.
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FAZLOOMAND, Ahmad Fazayel. "The Impact of Social Networks on Academic Achievement of Students: A Case Study of Badakhshan University Students." Integrated Journal for Research in Arts and Humanities 3, no. 2 (2023): 199–203. http://dx.doi.org/10.55544/ijrah.3.2.34.
Texte intégralRésumé :
Due to the increasing expansion of using social networks among people particularly students, the research in this field is a necessitate. This study aims to examine the impact of using social networks on the academic achievement of male students at Badakhshan University. The data for this research gathered through random sampling of 100 students of Badakhshan University who currently study in the academic years of 2022-2023. The students GPAs of past semester taken as the base to analyze the impact of social network usage and its effect on academic achievement, through which questionnaire designed. The data has been analyzed in SPSS applying one-way ANOVA. There are significant difference between the number of academic achievement of normal users of social network (with 15/13average and 2/01standerd deviation) and students with social media addiction (with 4/84average and 1/27standerd deviation) (p<0.01/0.05). Spending too much time on social media causes a decline in the hours of studying and exhaustion of students in the class. Therefore, it will affect the academic achievement to decline.
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Dexter, Darian. "Improve Social and Academic Innovation Through Governance Reform." International Journal of Science and Society 4, no. 3 (2022): 33–40. http://dx.doi.org/10.54783/ijsoc.v4i3.496.
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Governance Reform for Economic and Social Progress. Recent years have seen an increase in the number of research concentrating on interactive forms of governance, perhaps as a response to the growth of governance networks across all levels and policy domains. This study is an effort to further the field of governance studies by investigating the potential of governance networks to promote social and pedagogical advancements through collaboration. The study begins by outlining what governance networks are and then moves on to systematically reviewing the various ideas that attempt to account for their recent proliferation. Next, it offers a working definition of innovation and explores the ways in which networked cooperation fosters creative output. Finally, it explains how novel approaches to leadership and management can spark, foster, and catalyze collaborative innovation. Reform in the Classroom.