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  1. Research

    Stance and influence of Twitter users regarding the Brexit referendum

    Social media are an important source of information about the political issues, reflecting, as well as influencing, public mood. We present an analysis of Twitter data, collected over 6 weeks before the Brexit...

    Miha Grčar, Darko Cherepnalkoski, Igor Mozetič and Petra Kralj Novak

    Computational Social Networks 2017 4:6

    Published on: 24 July 2017

  2. Research

    Using attractiveness model for actors ranking in social media networks

    Influential actors detection in social media such as Twitter or Facebook can play a major role in gathering opinions on particular topics, improving the marketing efficiency, predicting the trends, etc.

    Ziyaad Qasem, Marc Jansen, Tobias Hecking and H. Ulrich Hoppe

    Computational Social Networks 2017 4:3

    Published on: 26 June 2017

  3. Research

    Measuring the value of accurate link prediction for network seeding

    The influence-maximization literature seeks small sets of individuals whose structural placement in the social network can drive large cascades of behavior. Optimization efforts to find the best seed set often as...

    Yijin Wei and Gwen Spencer

    Computational Social Networks 2017 4:1

    Published on: 18 May 2017

  4. Research

    Detection of strong attractors in social media networks

    Detection of influential actors in social media such as Twitter or Facebook plays an important role for improving the quality and efficiency of work and services in many fields such as education and marketing.

    Ziyaad Qasem, Marc Jansen, Tobias Hecking and H. Ulrich Hoppe

    Computational Social Networks 2016 3:11

    Published on: 7 December 2016

  5. Research

    Text normalization for named entity recognition in Vietnamese tweets

    Named entity recognition (NER) is a task of detecting named entities in documents and categorizing them to predefined classes, such as person, location, and organization. This paper focuses on tweets posted on...

    Vu H. Nguyen, Hien T. Nguyen and Vaclav Snasel

    Computational Social Networks 2016 3:10

    Published on: 1 December 2016

  6. Research

    Why continuous discussion can promote the consensus of opinions?

    Why group opinions tend to be converged through continued communication, discussion and interactions? Under the framework of the social influence network model, we rigorously prove that the group consensus is ...

    Zhenpeng Li, Xijin Tang, Benhui Chen, Jian Yang and Peng Su

    Computational Social Networks 2016 3:9

    Published on: 21 November 2016

  7. Research

    Real-time topic-aware influence maximization using preprocessing

    Influence maximization is the task of finding a set of seed nodes in a social network such that the influence spread of these seed nodes based on certain influence diffusion model is maximized. Topic-aware inf...

    Wei Chen, Tian Lin and Cheng Yang

    Computational Social Networks 2016 3:8

    Published on: 10 November 2016

  8. Research

    Information fusion-based approach for studying influence on Twitter using belief theory

    Influence in Twitter has become recently a hot research topic, since this micro-blogging service is widely used to share and disseminate information. Some users are more able than others to influence and persuade...

    Lobna Azaza, Sergey Kirgizov, Marinette Savonnet, Éric Leclercq, Nicolas Gastineau and Rim Faiz

    Computational Social Networks 2016 3:5

    Published on: 22 September 2016

  9. Research

    Factorization threshold models for scale-free networks generation

    Several models for producing scale-free networks have been suggested; most of them are based on the preferential attachment approach. In this article, we suggest a new approach for generating scale-free networ...

    Akmal Artikov, Aleksandr Dorodnykh, Yana Kashinskaya and Egor Samosvat

    Computational Social Networks 2016 3:4

    Published on: 22 August 2016

  10. Research

    A hashtag recommendation system for twitter data streams

    Twitter has evolved into a powerful communication and information sharing tool used by millions of people around the world to post what is happening now. A hashtag, a keyword prefixed with a hash symbol (#), i...

    Eriko Otsuka, Scott A. Wallace and David Chiu

    Computational Social Networks 2016 3:3

    Published on: 31 May 2016

  11. Research

    A game theory-based trust measurement model for social networks

    In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust i...

    Yingjie Wang, Zhipeng Cai, Guisheng Yin, Yang Gao, Xiangrong Tong and Qilong Han

    Computational Social Networks 2016 3:2

    Published on: 20 May 2016

  12. Research

    Optimization problems in correlated networks

    Solving the shortest path and min-cut problems are key in achieving high-performance and robust communication networks. Those problems have often been studied in deterministic and uncorrelated networks both i...

    Song Yang, Stojan Trajanovski and Fernando A. Kuipers

    Computational Social Networks 2016 3:1

    Published on: 22 January 2016

  13. Research

    Co-evolutionary dynamics in social networks: a case study of Twitter

    Complex networks often exhibit co-evolutionary dynamics, meaning that the network topology and the state of nodes or links are coupled, affecting each other in overlapping time scales. We focus on the co-evolu...

    Demetris Antoniades and Constantine Dovrolis

    Computational Social Networks 2015 2:14

    Published on: 31 July 2015

  14. Research

    The role of competitiveness in the Prisoner’s Dilemma

    Competitiveness is a relevant social behavior and in several contexts, from economy to sport activities, has a fundamental role. We analyze this social behavior in the domain of evolutionary game theory, using...

    Marco A Javarone and Antonio E Atzeni

    Computational Social Networks 2015 2:15

    Published on: 31 July 2015

  15. Research

    Distribution and dependence of extremes in network sampling processes

    We explore the dependence structure in the sampled sequence of complex networks. We consider randomized algorithms to sample the nodes and study extremal properties in any associated stationary sequence of cha...

    Konstantin Avrachenkov, Natalia M. Markovich and Jithin K. Sreedharan

    Computational Social Networks 2015 2:12

    Published on: 22 July 2015

  16. Research

    Network approach to internet bandwidth distributions

    This study examines the communications networks formed by direct international Internet links, weighted by bandwidth capacity, each year over the 2002–2011 period. Specifically, we analyze changes in bandwidth...

    Hyunjin Seo and Stuart Thorson

    Computational Social Networks 2015 2:11

    Published on: 19 July 2015

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