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SAMD: A System for Abnormal Messages Detection Oriented Microblog Message Stream

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Bio-Inspired Computing -- Theories and Applications (BIC-TA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 562))

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Abstract

Microblog has been an important medium for providing the rapid communications of public opinion and can quickly publicize a burst topic for discussion when unexpected incidents happen. Abnormal messages are usually the source of burst topics and are important for the diffusion of burst topics. It is necessary to detect abnormal messages from microblog real-time message stream. In this paper, we propose SAMD, a System for Abnormal Messages Detection. In SAMD, sliding time window model is applied to divide the microblog data stream into different shards. Only that the participation of messages exceed initial threshold can be indexed and stored in two-level hash table. An efficient abnormal messages detection model is used to detect abnormal messages in a given time window. The case study on the collected data set can show that SAMD is effective to detect and demonstrate abnormal messages from large-scale microblog message stream.

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Acknowledgment

The authors would like to thank the reviewers for suggesting many ways to improve the paper. This work was partially supported by the National High Technology Research and Development Program of China (No. 2012AA012802), the Fundamental Research Funds for the Central Universities (No. HEUCF100605) and the National Natural Science Foundation of China (No. 61170242, 60633020, and 61300206).

Author information

Authors and Affiliations

  1. Information Security Research Center, Harbin Engineering University, Harbin, China

    Guozhong Dong, Wu Yang & Wei Wang

  2. National Computer Network Emergency Response Technical Team/Coordination Center, Beijing, China

    Bo Wang

  3. Daqing Lvyuan Wind Power Generation CO., LTD, Daqing, China

    Rui Sun

Authors
  1. Guozhong Dong
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  2. Bo Wang
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  3. Wu Yang
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  4. Wei Wang
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  5. Rui Sun
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Corresponding author

Correspondence to Wu Yang .

Editor information

Editors and Affiliations

  1. Xidian University, Xi'an, China

    Maoguo Gong

  2. Huazhong Univ. of Science and Technology, Wuhan, China

    Pan Linqiang

  3. University of Petroleum, Qingdao, China

    Song Tao

  4. University of Science and Technology of China, Hefei, China

    Ke Tang

  5. Anhui University, Hefei, China

    Xingyi Zhang

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© 2015 Springer-Verlag Berlin Heidelberg

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Dong, G., Wang, B., Yang, W., Wang, W., Sun, R. (2015). SAMD: A System for Abnormal Messages Detection Oriented Microblog Message Stream. In: Gong, M., Linqiang, P., Tao, S., Tang, K., Zhang, X. (eds) Bio-Inspired Computing -- Theories and Applications. BIC-TA 2015. Communications in Computer and Information Science, vol 562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49014-3_11

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  • DOI: https://doi.org/10.1007/978-3-662-49014-3_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49013-6

  • Online ISBN: 978-3-662-49014-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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