Blog Rating as an Iterative Collaborative Process

Louta, Malamati; Varlamis, Iraklis

doi:10.1007/978-3-642-11684-1_11

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…Additionally, our model supports trust propagation through explicit user connections in the social network. Moreover, combining the merits of our previous work on social network dynamics [9], [10], we incorporate the element of time in the calculation of the users' reputation. Finally, the proposed model is generic, in that it can he readily applied to any type of social network, including blogs, social networking applications, microblogging sites, etc.…”

Section: Related Workmentioning

confidence: 99%

“…This is particularly important since the rapid increase in terms of content and users of social media shifts the problem of information search to that of information discovery. The largest body of work in this area generates overall rankings [6], [7], [8] and only recently there have been some efforts in personalizing the ranking [9] and in providing different rankings depending on the scope under which the network is examined [10], [11], [12].…”

Section: Introductionmentioning

confidence: 99%

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A Trust-Aware System for Personalized User Recommendations in Social Networks

Eirinaki

Louta

Varlamis

2014

IEEE Trans. Syst. Man Cybern, Syst.

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Social network analysis has recently gained a lot of interest because of the advent and the increasing popularity of social media, such as blogs, social networking applications, micro-blogging, or customer review sites. In this environment, trust is becoming an essential quality among user interactions and the recommendation for useful content and trustful users is crucial for all the members of the network. In this work, we introduce a framework for handling trust in social networks, which is based on a reputation mechanism that captures the implicit and explicit connections between the network members, analyzes the semantics and dynamics of these connections and provides personalized user recommendations to the network members.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Trust-Aware System for Personalized User Recommendations in Social Networks

Eirinaki

Louta

Varlamis

2014

IEEE Trans. Syst. Man Cybern, Syst.

Self Cite

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“…wrong or biased reviews, misleading tags), the emerging rating and recommendation schemes [12] employ reputation mechanisms, which prioritize long-living content and long-term contribution [1]. The collaborative rating model, which was designed for content filtering and personalization [13] has recently been employed for ranking content based on popularity and interestingness [16] or for evaluating content quality in general [14]. Digg 8 is a Web 2.0 application that allows users to report online web content (news, blogs, videos etc) and let other users rate them by voting on them.…”

Section: Content Quality Control and Assurancementioning

confidence: 99%

Quality of Content in Web 2.0 Applications

Varlamis

2010

Knowledge-Based and Intelligent Information and Engineering Systems

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Abstract. Nowadays, web users are facing a novel and dynamically changing environment, which promotes collaboration in content creation. In the web era, people usually neglected the quality of content, and had minimum authority on reporting good or bad content, whereas, in Web 2.0, content is becoming a priority and people become more critical when they assess its quality. In the former case, each web site had an identity, a single editor or a closed group of editors, who were responsible for content quality management and the stylistic design was the main quality standard for visitors. In the latter case, several applications and a new way of thinking have changed the workplace and created a new approach to quality management. Specifically, the team of editors is open to every web user, content is a collaborative product and the "embedded object" or "inline linking" model is gaining in popularity against hyperlinking.

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Blog Rating as an Iterative Collaborative Process

Cited by 6 publications

References 8 publications

A Trust-Aware System for Personalized User Recommendations in Social Networks

A Trust-Aware System for Personalized User Recommendations in Social Networks

Quality of Content in Web 2.0 Applications

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