Social community detection and message propagation scheme based on personal willingness in social network

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Personal willingness is one of the most important factors influencing the construction of social community and the message propagation in social network. Personal willingness is used to describe the subjective initiative of node (user) to communicate information with outside world. The personal willingness is greater, the corresponding user is more willing to make communication with outside world, then the user is more likely to join the corresponding community. So, personal willingness may reduce the probability of generating large-scale communities so as to improve the accuracy and reliability of community detection and increase the stability of community structure. This paper proposes a social community detection and message propagation scheme based on personal willingness in social network. In the proposed scheme, the social community detection algorithm extracts node attributes and then uses modularity degree, interest degree and personal willingness to sophisticatedly detect social communities; also, the message propagation method is based on the exponential model, which constructs feature vector by edge feature and node feature, willingness vector by personal willingness and community willingness, and related basic relationship by propagation probability and propagation delay. Based on the Weibo, YouTube and Digg data, the experiments show that our proposed scheme can ensure the stability and reliability of social community detection and add the initiative and effectiveness of message propagation among users.

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  1. 1.

    In China, Weibo is a kind of social software provided by the SINA corporation, which is widely used by young people.

  2. 2.

    To extract some features whose values are not the interval [0, 1], we may use the min-max standardization method to process the features. Also, other features may be directly got according to the related definitions or formulas.

  3. 3.

    The URL links to a network page that allows more detailed or comprehensive interpretation of the message content.

  4. 4.

    The content of the label information can attract more readers’ attention or generate interest similarity.

  5. 5.

    In this paper, we use lexical items to construct document vector.

  6. 6.

    We may prove the function \(F(C|\alpha ,\beta )\) has the continuous first-order partial derivatives on \(\alpha \) and \(\beta \).

  7. 7.

    The Sina company is a big network company, which provides many functions of Web site portal.


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Funding was provided by National Natural Science Foundations of China (No. 61402055, No. 61504013), Hunan Provincial Natural Science Foundation of China (No. 2018JJ2445, No. 2016JJ3012) and Scientific Research Project of Hunan Provincial Education Department (No. 15C0041, No. 12C0010).

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Correspondence to Ke Gu.

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Gu, K., Wang, L. & Yin, B. Social community detection and message propagation scheme based on personal willingness in social network. Soft Comput 23, 6267–6285 (2019).

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  • Social network
  • Personal willingness
  • Community detection
  • Message propagation