Taking Social Networks to the Next Level

Dingli, Alexiei; Seychell, Dylan

doi:10.4018/jdst.2012100103

Cited by 8 publications

(4 citation statements)

References 14 publications

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“…This is an open JSON format specification for the syndication of activities performed in social web applications and services. It is currently developed by the Social Web Working Group of the W3C (http://www.w3.org/wiki/Activity_Streams/) for facilitating the integration of social activities performed on diverse sites (Dingli and Seychell, 2012).…”

Section: Social Activities and Interoperabilitymentioning

confidence: 99%

Blogracy

Franchi

Poggi

Tomaiuolo

2016

International Journal of Distributed Systems and Technologies

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The current approach to build social networking systems is to create huge centralized systems owned by a single company. However, such strategy has many drawbacks, e.g., lack of privacy, lack of anonymity, risks of censorship and operating costs. In this paper the authors propose a novel P2P system that leverages existing, widespread and stable technologies such as DHTs and BitTorrent. In particular, they introduce a key-based identity system and a model of social relations for distributing content efficiently among interested readers. The system they propose, Blogracy, is a micro-blogging social networking system focused on: (i) anonymity and resilience to censorship; (ii) authenticatable content; (iii) semantic interoperability using activity streams. The authors have implemented the system and conducted various experiments to study its behaviour. The results are presented here, regarding (i) communication delays for some simulations of node churn, (ii) delays measured in test operations over PlanetLab, in direct communication, and (iii) through the I2P anonymizing network.

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Section: Social Activities and Interoperabilitymentioning

confidence: 99%

Blogracy

Franchi

Poggi

Tomaiuolo

2016

International Journal of Distributed Systems and Technologies

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“…Recently, social network integration has drawn attention among researchers. An adaptive social network integrator called SNAP was proposed to amalgamate various social networks (Facebook, Twitter, and Flickr) in one adaptive environment, which sorted the users' feed according to their preference (Dingli & Seychell, 2012). Besides, a novel pervasive community was explored by Lima et al (2014) to support collaboration in pervasive environments, which took into accounts not only individual interests, but also the collective and social context.…”

Section: Social Network Detectionmentioning

confidence: 99%

Modeling and Analyzing of Research Topic Evolution Associated with Social Networks of Researchers

Liang

Jin

et al. 2016

International Journal of Distributed Systems and Technologies

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Research trends keep evolving along the time with certain trackable patterns. Mining academic literature and discovering the latent research trends evolution is an interesting and important problem. Few of previous studies focusing on academic topic evolution modeling have addressed the temporal topic evolution patterns. In addition, researchers' profile and their social networks are valuable complementary to the research trends tracking. In this study, to analyze the underlying research trends evolution along with the scientific collaborations of researchers, a novel temporal research trends evolution model associated with researchers' social networks is proposed and built. Specifically, the detected research topics are classified into different clusters in each timeslot, and the evolution patterns are deduced among these topic clusters. The effectiveness of our approach is evaluated based on a real academic dataset. The experimental results can help users to discover the major research trends for specific fields. Besides, the tracked statuses of the corresponding scientific groups are helpful for searching research trends or finding collaboration opportunities according to researchers' different requirements.

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“…As known by everyone, social networks have become inseparable part of every life (Dingli & Seychell, 2012). Related works point out mobile social networks as a smart ecosystem to harvest data from smart mobile devices in a participatory manner (Hu, Li, Ngai, Leung, & Kruchten, 2014).…”

Section: Introductionmentioning

confidence: 99%

Sonata

Kantarcı

Carr

Pearsall

2016

International Journal of Distributed Systems and Technologies

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With the advent of mobile cloud computing paradigm, mobile social networks (MSNs) have become attractive tools to share, publish and analyze data regarding everyday behavior of mobile users. Besides revealing information about social interactions between individuals, MSNs can assist smart city applications through crowdsensing services. In presence of malicious users who aim at misinformation through manipulation of their sensing data, trustworthiness arises as a crucial issue for the users who receive service from smart city applications. In this paper, the authors propose a new crowdsensing framework, namely Social Network Assisted Trustworthiness Assurance (SONATA) which aims at maximizing crowdsensing platform utility and minimizing the manipulation probability through vote-based trustworthiness analysis in dynamic social network architecture. SONATA adopts existing Sybil detection techniques to identify malicious users who aim at misinformation/disinformation at the crowdsensing platform. The authors present performance evaluation of SONATA under various crowdsensing scenarios in a smart city setting. Performance results show that SONATA improves crowdsensing utility under light and moderate arrival rates of sensing task requests when less than 7% of the users are malicious whereas crowdsensing utility is significantly improved under all task arrival rates if the ratio of malicious users to the entire population is at least 7%. Furthermore, under each scenario, manipulation ratio is close to zero under SONATA while trustworthiness unaware recruitment of social network users leads to a manipulation probability of 2.5% which cannot be tolerated in critical smart city applications such as disaster management or public safety.

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Taking Social Networks to the Next Level

Cited by 8 publications

References 14 publications

Blogracy

Blogracy

Modeling and Analyzing of Research Topic Evolution Associated with Social Networks of Researchers

Sonata

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