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TEAMS SIGNED

Modelling Trust-based Evolutionary Dynamics in Signed Social Networks

Total Cost €

EC-Contrib. €

Partnership

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TEAMS project word cloud

Explore the words cloud of the TEAMS project. It provides you a very rough idea of what is the project "TEAMS" about.

pioneer massive capturing theoretical users extensive patterns trust benefit relations communities mechanism distrust dynamic evolutions broaden model practical detection foundation signed will recommendation epinions solid media prosperity ebay portfolio world computing evolutionary multiple learning techniques lay evolution personalized explore dynamics networks host soft disciplines social horizon formal guidance representation complicates significantly fundamentals detecting directions china skills networking interactions complexity fellow algorithms university transfer career trusted training stimulate leads fca valuable collaborations innovative diversity mechanisms identification collaborative series witnesses corresponding ssns opinion imparted

Project "TEAMS" data sheet

The following table provides information about the project.

Coordinator	THE UNIVERSITY OF EXETER Organization address address: THE QUEEN'S DRIVE NORTHCOTE HOUSE city: EXETER postcode: EX4 4QJ website: www.ex.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	United Kingdom [UK]
Total cost	224˙933 €
EC max contribution	224˙933 € (100%)
Programme	1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
Code Call	H2020-MSCA-IF-2018
Funding Scheme	MSCA-IF-EF-ST
Starting year	2020
Duration (year-month-day)	from 2020-02-01 to 2022-01-31

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	THE UNIVERSITY OF EXETER THE UNIVERSITY OF EXETER Organization address address: THE QUEEN'S DRIVE NORTHCOTE HOUSE city: EXETER postcode: EX4 4QJ website: www.ex.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (EXETER)	coordinator	224˙933.00

Map

Project objective

Users’ experience with real-world social systems (e.g., Epinions and eBay) witnesses the importance of Signed Social Networks (SSNs) that have wide practical and valuable applications in social media such as opinion guidance, personalized recommendation, and topic identification. However, the diversity of massive social interactions complicates the trust and distrust relations among users in SSNs. In particular, the complexity of distrust relations leads to significant challenges in detecting the trusted communities and capturing their evolutionary patterns.

This research aims to pioneer the innovative mechanisms for detecting the trusted communities and learning the evolutionary dynamics. To this end, we will explore the representation mechanism for SSNs by using the Formal Concept Analysis (FCA) and develop a FCA-based representation model. Next, the mechanisms and corresponding algorithms for detecting trusted communities and identifying their dynamic evolutions will be investigated. This research will provide both theoretical fundamentals and practical techniques for detection and dynamic evolution of trusted communities in SSNs. Moreover, this project can stimulate new research directions and the collaborative opportunities across multiple disciplines, such as social computing, soft computing and networking.

To broaden the fellow’s knowledge horizon, a series of research, training, and knowledge transfer activities are planned. The new knowledge and skills imparted in these activities will further promote the applicant’s research portfolio and significantly enhance his career prosperity. The research will also lay a solid foundation for the long-term and wide-range collaborations between the fellow and the host university, and eventually lead to more extensive and higher impact of research results, from which both EU and China will benefit.

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The information about "TEAMS" are provided by the European Opendata Portal: CORDIS opendata.