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Journal of Software Engineering
  Year: 2016 | Volume: 10 | Issue: 4 | Page No.: 338-346
DOI: 10.3923/jse.2016.338.346
The Research of Micro-blog Influence Evaluation of Automobile Recall Information
Yu Lijuan, Song Li and Ren Chenmei

Abstract:
Background: The micro-bloginfluenceof automobile recall information has become an important factor in causing social unrest. This study researches the comprehensive evaluation method of the micro-blog influence, constructs the influence evaluation indicator system, establishes the influence monitoring anticipation mechanism and provides the timely warning for the automobile recall supervisory department to monitor the situation. Materials and Methods: Considering the interests and game about automobile recall information spread of three types of micro-blog users who are the manufacturers, consumers and the third party supervision mechanism, using literature review, questionnaire survey, the hierarchy analytic process and so on, the study chose the evaluation indicators and evaluation method of the micro-blog influence of the automobile recall information and sets up the influence index to provide the four grades warning mechanism. Results: The method was applied to evaluate the Sina micro-blog influence at some point and found that it can reflect the influence tendency of micro-blog user and the basic state of the current domestic automobile recalls events in micro-blog spread influence: The influence of media users is the largest and the influence of industry, business and personal users is smaller. Conclusion: The established indicators and its significance partly support the existing research, at the same time, this study enriches the field of micro-blog research, develops the application space of micro-blog influence and there is certain application value from the assessment results.
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How to cite this article:

Yu Lijuan, Song Li and Ren Chenmei, 2016. The Research of Micro-blog Influence Evaluation of Automobile Recall Information. Journal of Software Engineering, 10: 338-346.

DOI: 10.3923/jse.2016.338.346

URL: https://scialert.net/abstract/?doi=jse.2016.338.346

 
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