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Survey on Sina Weibo Research Based on Big Data Mining

Received: 24 July 2015     Accepted: 31 July 2015     Published: 1 August 2015
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Abstract

In recent years, with the advances in information communication, Sina Weibo has attracted the attention of scholars in China. The big data analytics platform at Sina Weibo has experienced tremendous growth over the past few years in terms of size, complexity, number of users and variety of use cases. Without a clear description of how the underlying data were collected, stored, cleaned, and analyzed, however, Weibo network analysis and modeling become difficult. To analyze the Weibo data, the structure framework of Weibo need firstly be known, and the composition and characteristics of Weibo data must be understood. Then by comparing different application programming interface (API), the more efficient and convenient method of data collection are found. Moreover, according to the characteristics of Weibo data, quarrying the cleaning methods and strategies provide convenient for the further processing of data. Finally, the integration of big data mining and the properties of Weibo find the most effective method based on large Weibo data, and discuss the future research

Published in International Journal of Data Science and Analysis (Volume 1, Issue 1)
DOI 10.11648/j.ijdsa.20150101.11
Page(s) 1-7
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

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Keywords

Sina Weibo, Big Data, Analytics Platform, API, Data Mining

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    Ru Wang. (2015). Survey on Sina Weibo Research Based on Big Data Mining. International Journal of Data Science and Analysis, 1(1), 1-7. https://doi.org/10.11648/j.ijdsa.20150101.11

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    Ru Wang. Survey on Sina Weibo Research Based on Big Data Mining. Int. J. Data Sci. Anal. 2015, 1(1), 1-7. doi: 10.11648/j.ijdsa.20150101.11

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    Ru Wang. Survey on Sina Weibo Research Based on Big Data Mining. Int J Data Sci Anal. 2015;1(1):1-7. doi: 10.11648/j.ijdsa.20150101.11

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  • @article{10.11648/j.ijdsa.20150101.11,
      author = {Ru Wang},
      title = {Survey on Sina Weibo Research Based on Big Data Mining},
      journal = {International Journal of Data Science and Analysis},
      volume = {1},
      number = {1},
      pages = {1-7},
      doi = {10.11648/j.ijdsa.20150101.11},
      url = {https://doi.org/10.11648/j.ijdsa.20150101.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20150101.11},
      abstract = {In recent years, with the advances in information communication, Sina Weibo has attracted the attention of scholars in China. The big data analytics platform at Sina Weibo has experienced tremendous growth over the past few years in terms of size, complexity, number of users and variety of use cases. Without a clear description of how the underlying data were collected, stored, cleaned, and analyzed, however, Weibo network analysis and modeling become difficult. To analyze the Weibo data, the structure framework of Weibo need firstly be known, and the composition and characteristics of Weibo data must be understood. Then by comparing different application programming interface (API), the more efficient and convenient method of data collection are found. Moreover, according to the characteristics of Weibo data, quarrying the cleaning methods and strategies provide convenient for the further processing of data. Finally, the integration of big data mining and the properties of Weibo find the most effective method based on large Weibo data, and discuss the future research},
     year = {2015}
    }
    

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    T1  - Survey on Sina Weibo Research Based on Big Data Mining
    AU  - Ru Wang
    Y1  - 2015/08/01
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    AB  - In recent years, with the advances in information communication, Sina Weibo has attracted the attention of scholars in China. The big data analytics platform at Sina Weibo has experienced tremendous growth over the past few years in terms of size, complexity, number of users and variety of use cases. Without a clear description of how the underlying data were collected, stored, cleaned, and analyzed, however, Weibo network analysis and modeling become difficult. To analyze the Weibo data, the structure framework of Weibo need firstly be known, and the composition and characteristics of Weibo data must be understood. Then by comparing different application programming interface (API), the more efficient and convenient method of data collection are found. Moreover, according to the characteristics of Weibo data, quarrying the cleaning methods and strategies provide convenient for the further processing of data. Finally, the integration of big data mining and the properties of Weibo find the most effective method based on large Weibo data, and discuss the future research
    VL  - 1
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Author Information
  • School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, PR China

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