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Social Networking in Education

Niall McCarroll, Kevin Curran
2013 International Journal of Innovation in the Digital Economy  
While undoubtedly, due to the very casual nature of social networking, there are serious concerns over how it could be integrated in a learning environment; the potential positive outcomes are many and  ...  To date realising the potential of Social Networking Sites (SNSs) beyond their leisure uses has been severely restricted in a number of areas.  ...  The public forums provided via Blogs, Wikis and Social Networks, promote and agitate debate acting as a catalyst in the generation and refinement of information.  ... 
doi:10.4018/jide.2013010101 fatcat:o6nerifvynbtvmpkkp7habaglu

Pixel-Oriented Network Visualization: Static Visualization of Change in Social Networks [chapter]

Klaus Stein, René Wegener, Christoph Schlieder
2012 Lecture Notes in Social Networks  
The visualization is exemplified using social networks based on corporate wikis.  ...  We propose a novel approach for the visualization of user interactions in social networks: a pixeloriented visualization of a graphical network matrix where activity timelines are folded to inner glyphs  ...  fits on the screen or paper at once.  ... 
doi:10.1007/978-3-7091-1346-2_5 dblp:series/lnsn/SteinWS13 fatcat:m7rcblknlbaihe6abyy52niksa

Cooperation Systems in Research Networks - Case Evidence of Network (Mis)Fit and Adoption Challenges

Kai Riemer, Jan vom Brocke, Daniel Richter, Stefan Große Böckmann
2008 European Conference on Information Systems  
A social network analysis further uncovers that the GARNET network is very fragmented on the social level, which points to a misfit between network structure and the positioning of the collaboration platform  ...  As part of its 6 th research framework, the European Commission (EC) funded a total of 130 so called networks of excellence (NoEs), a special kind of network with the purpose of strengthening and developing  ...  Because of this, the distribution of objects (documents, wikis, newsgroup content or chat objects) across the resource tree gives good insight as to the purpose the collaboration platform served for the  ... 
dblp:conf/ecis/RiemerBRB08 fatcat:ie7ucineibe3laj6mdhqbpwolm

Enterprise Social Networking: Opportunities, Adoption, and Risk Mitigation

Efraim Turban, Narasimha Bolloju, Ting-Peng Liang
2011 Journal of Organizational Computing and Electronic Commerce  
Once a social networking project is considered to provide a good fit and to be organizationally viable, the firm needs to develop a good deployment strategy for its adoption based on our proposed process  ...  For example, a business intending to use wikis for information sharing can be a high fit, but using microblogs for knowledge management may be considered a low fit.  ... 
doi:10.1080/10919392.2011.590109 fatcat:aceoqtcj2jbqpie76pjudhqwpi

Common Growth Patterns for Regional Social Networks: a Point Process Approach [article]

Tiandong Wang, Sidney I. Resnick
2019 arXiv   pre-print
Although recent research on social networks emphasizes microscopic dynamics such as retweets and social connectivity of an individual user, we focus on macroscopic growth dynamics of social network link  ...  Empirical findings suggest that the startup phase of a regional network can be modeled by a self-exciting point process.  ...  Using a point process approach, we observe some common patterns of network growth in regional social networks.  ... 
arXiv:1911.07902v1 fatcat:q2w3tgnl3rgy7af3to2cnvnbgq

Trustworthy distributed computing on social networks

Abedelaziz Mohaisen, Huy Tran, Abhishek Chandra, Yongdae Kim
2013 Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security - ASIA CCS '13  
We investigate a new computing paradigm, called SocialCloud, in which computing nodes are governed by social ties driven from a bootstrapping trust-possessing social graph.  ...  We propose metrics for measuring the utility and advantage of this computing paradigm, and using real-world social graphs and structures of social traces; we investigate the potential of this paradigm  ...  Most importantly, our paradigm exploits the trust exhibited in social networks as a guarantee for the good behavior of other "workers" in the system.  ... 
doi:10.1145/2484313.2484332 dblp:conf/ccs/MohaisenTCK13 fatcat:3wtvx2rtfrh7pllmkdjrp4wgz4

Common Growth Patterns for Regional Social Networks: A Point Process Approach

Tiandong Wang, Sidney I. Resnick
2021 Journal of Data Science  
In this paper, we study macroscopic growth dynamics of social network link formation.  ...  Rather than focusing on one particular dataset, we find invariant behavior in regional social networks that are geographically concentrated.  ...  Acknowledgement The authors would like to thank two anonymous referees and editors for their valuable comments on the manuscript.  ... 
doi:10.6339/21-jds1021 fatcat:7udfueq5fzaxhigdqp2iyhm6nq

Hyperbolic Node Embedding for Signed Networks [article]

Wenzhuo Song, Hongxu Chen, Xueyan Liu, Hongzhe Jiang, Shengsheng Wang
2020 arXiv   pre-print
We also propose a non-Euclidean signed network embedding method based on structural balance theory and Riemannian optimization, which embeds signed networks into a Poincar\'e ball in a hyperbolic space  ...  In this work, we answer an open question that whether the hyperbolic space is a better choice to accommodate signed networks and learn embeddings that can preserve the corresponding special characteristics  ...  Two general statistical characteristics are widely found in real-world networks: a) scale-free 12 which refers to the degree distribution of a network follows a power-law distribution p(k) = k −γ , where  ... 
arXiv:1910.13090v2 fatcat:yrqagsg3zzhnlofkkpnft7gs4a

Adversarial Network Embedding [article]

Quanyu Dai, Qiang Li, Jian Tang, Dan Wang
2017 arXiv   pre-print
Learning low-dimensional representations of networks has proved effective in a variety of tasks such as node classification, link prediction and network visualization.  ...  ., a structure preserving component and an adversarial learning component.  ...  Liang Zhang of Data Science Lab at and Prof. Xiaoming Wu of The Hong Kong Polytechnic University for their valuable discussion. Dan Wang's work is supported in part by HK PolyU G-YBAG.  ... 
arXiv:1711.07838v1 fatcat:urnmryjidfgr3di4znm6dh2p2u

Adversarial Network Embedding

Quanyu Dai, Qiang Li, Jian Tang, Dan Wang
Learning low-dimensional representations of networks has proved effective in a variety of tasks such as node classification, link prediction and network visualization.  ...  ., a structure preserving component and an adversarial learning component.  ...  Liang Zhang of Data Science Lab at and Prof. Xiaoming Wu of The Hong Kong Polytechnic University for their valuable discussion. Dan Wang's work is supported in part by HK PolyU G-YBAG.  ... 
doi:10.1609/aaai.v32i1.11865 fatcat:6mqe7abs4fcrdaje364dwylmsy


2014 Issues in Information Systems  
Social media has become a central point of a person's daily life for many people around the world with the ability to be connected to these sites through access to cellphones, tablets, and computers.  ...  That being said, the use of information that is supplied to anyone and everyone on a social media site creates major concerns about individual privacy and concerns about how this information can and is  ...  [12] Social and Professional Networking "A social networking service is a platform to build social networks or social relations among people who, for example, share interests, activities, backgrounds  ... 
doi:10.48009/2_iis_2014_103-109 fatcat:xxyrw4svvrcdrn4hcd2na456ku

Sampling social networks using shortest paths

Alireza Rezvanian, Mohammad Reza Meybodi
2015 Physica A: Statistical Mechanics and its Applications  
. a b s t r a c t In recent years, online social networks (OSN) have emerged as a platform of sharing variety of information about people, and their interests, activities, events and news from real worlds  ...  The sampled network is then computed as a subgraph of the social network which contains a percentage of highly ranked edges.  ...  A good study for sampling from complex networks presented by Leskovec et al. [15] .  ... 
doi:10.1016/j.physa.2015.01.030 fatcat:myd2wjt7vnedzk2piicmathrzy

Characterizing interactions in online social networks during exceptional events

Elisa Omodei, Manlio De Domenico, Alex Arenas
2015 Frontiers in Physics  
In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event  ...  Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics.  ...  To a certain extent, online interactions represent a good proxy for social interactions and, as a consequence, the possibility to track the activity of individuals in online social networks allows one  ... 
doi:10.3389/fphy.2015.00059 fatcat:ptfzcpnukjdqrm27dsjsa63k3e

Reasons for Using Social Networks Professionally [chapter]

Anne Kathrin Schaar, André Calero Valdez, Martina Ziefle, Denise Eraßme, Ann-Kathrin Löcker, Eva-Maria Jakobs
2014 Lecture Notes in Computer Science  
network usage.  ...  Findings show that both factors age and gender reveal a relatively low influence on the factors evaluation of usage motives, tools (as a measure for motivation), and incentives/reinforcements for social  ...  The studies from the "iNec" project have been funded by the German Ministry of Education and Research (BMBF) and the European Social Fund (ESF) within the program "Innovationsfähigkeit im demographischen  ... 
doi:10.1007/978-3-319-07632-4_37 fatcat:6xeof73ubfcullvx6lp75b3e24

Understanding Social Networks Using Transfer Learning

Jun Sun, Steffen Staab, Jerome Kunegis
2018 Computer  
A detailed understanding of users contributes to the understanding of the Web's evolution, and to the development of Web applications.  ...  Akin to human transfer of experiences from one domain to the next, transfer learning as a subfield of machine learning adapts knowledge acquired in one domain to a new domain.  ...  The research leading to these results has received funding from the European Community's Horizon 2020 -Research and Innovation Framework Programme under grant agreement No. 770469, CUTLER.  ... 
doi:10.1109/mc.2018.2701640 fatcat:efuegsdotvhtvg5uq3eksak4ry
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