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A blog ranking algorithm using analysis of both blog influence and characteristics of blog posts

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Abstract

In recent years, with the increasing number of blogs to share information, the ratio of blogs on the World Wide Web has been raised. In this regard, the problem of information quality has come up due to the rapidly increasing amount of information in a blogosphere. Therefore, discovering good quality information is one of the significant issues in the blog space. In this paper, we propose an algorithm for efficient blog ranking, called WCT (a blog ranking algorithm using Weighted Comments and Trackbacks). This method performs a ranking process through not only interconnection analysis of blogs but also structural weights for contents in the blogs. Moreover, we conduct performance evaluation and discuss the performance between our algorithm and a previous algorithm by comparing their experimental results, which show that our approach has higher performance than that of the other blog retrieval method.

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Acknowledgements

This research was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF Nos. 2013005682 and 20080062611).

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Authors and Affiliations

  1. Department of Computer Engineering, Sejong University, Seoul, Republic of Korea

    Jiwon Kim, Unil Yun, Gwangbum Pyun, Heungmo Ryang & Gangin Lee

  2. Department of Electronics Engineering, Konkuk University, Seoul, Republic of Korea

    Eunchul Yoon

  3. Department of Computer Science, Chungbuk National University, Cheongju, Republic of Korea

    Keun Ho Ryu

Authors
  1. Jiwon Kim
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  2. Unil Yun
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  3. Gwangbum Pyun
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  4. Heungmo Ryang
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  5. Gangin Lee
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  6. Eunchul Yoon
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  7. Keun Ho Ryu
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Correspondence to Unil Yun.

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Kim, J., Yun, U., Pyun, G. et al. A blog ranking algorithm using analysis of both blog influence and characteristics of blog posts. Cluster Comput 18, 157–164 (2015). https://doi.org/10.1007/s10586-013-0337-9

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  • DOI: https://doi.org/10.1007/s10586-013-0337-9

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