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Differential Information Diffusion Model in Social Network

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Intelligent Information and Database Systems (ACIIDS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10751))

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Abstract

A social network is modeled as a graph of nodes connected through interactions among users, an important medium for the information spreading and influence on users dynamically. Modeling information diffusion is still key problem to predict influences of information on users. In recent years, numerous literatures have proposed models to solve this problem. However, each of models is coming from different points of view. Based on differential equations and with a real mechanism of transferring, exchanging information in network, in this paper, it is proposed a model of temporal-spatial information diffusion, named differential information diffusion or DID model. This model is setup in accordance with topological structure of network, semantic content and interactive activities of users in network. Experimental computations show the feasibility of the proposed model, conformity with network topology and with prospects of scalability for large networks.

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Author information

Authors and Affiliations

  1. HCMC University of Technology and Education, Thu Duc, Ho Chi Minh City, Vietnam

    Hong T. Tu

  2. University of Information Technology, VNU-HCM, Thu Duc, Ho Chi Minh City, Vietnam

    Khu P. Nguyen

Authors
  1. Hong T. Tu
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  2. Khu P. Nguyen
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Corresponding authors

Correspondence to Hong T. Tu or Khu P. Nguyen .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Quang Binh University, Dong Hoi City, Vietnam

    Duong Hung Hoang

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Rutgers University, Piscataway, New Jersey, USA

    Hoang Pham

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Tu, H.T., Nguyen, K.P. (2018). Differential Information Diffusion Model in Social Network. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10751. Springer, Cham. https://doi.org/10.1007/978-3-319-75417-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-75417-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75416-1

  • Online ISBN: 978-3-319-75417-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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