earticle

논문검색

Predicting Information Popularity Degree in Microblogging Diffusion Networks

초록

영어

Microblogs have rapidly become the most popular means by which people communicate with friends, pay close attention to celebrity at any time. Hence many studies on microblogging networks have been done recently, focusing on information diffusion, popularity prediction, topic detection and more. In this paper, we study the popularity of tweets in microblogging networks and introduce a novel concept “popularity degree” that help divide microblogging into four levels. Through the empirical analysis of different popularity degree, we find the retweeting information of a tweet at an earlier time can help predict its final popularity. Hence we propose a prediction model based on SVM with the retweeting information within one hour. Experimental results show our model has better ability of prediction.

목차

Abstract
 1. Introduction
 2. Related work
 3. Empirical Analysis
  3.1. Dataset Description
  3.2. Observation and Findings
 4. Modeling Popularity Degree
  4.1. Model
  4.2. Feature Description and Scoring
 5. Experiment
  5.1. Scale
  5.2. Result
 6. Conclusion
 Acknowledgements
 References

저자정보

  • Wang Jiang College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
  • Wang Li College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
  • Wu Weili College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.