earticle

논문검색

Prediction of Users Retweet Times in Social Network

초록

영어

In view of the fact that the propagation path topology cannot effectively deal with complex social network consists of hundreds of millions of users. More researchers choose to use machine learning methods to complete retweet prediction. Those use the classification method to judge whether a message will be retweeted or not. This paper argues that retweet prediction should be regression analysis problem, not just the classification problem. Through collecting user characteristics on Twitter and selecting some features which have an important impact on the retweet behavior, a Prediction algorithm Based on the Logistic Regression for users Retweet Times in social network was proposed. Experiment results based on the actual data set show the regression analysis predicting model has a good predicting accuracy in dealing with retweet predicting, the proposed method is effectiveness.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Retweet Predicting based on Regression Analysis
 4. Experiments
 5. Conclusion
 Acknowledgements
 References

저자정보

  • Haihao Yu Heilongjiang Institute of Technology, Harbin, China
  • Xu Feng Bai Heilongjiang Institute of Technology, Harbin, China
  • ChengZhe Huang Heilongjiang Institute of Technology, Harbin, China
  • Haoliang Qi Heilongjiang Institute of Technology, Harbin, China

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.