Hot Topic Prediction Scheme Considering User Influences in Social Networks

소셜 네트워크에서 사용자의 영향력을 고려한 핫 토픽 예측 기법

  • 노연우 (충북대학교 정보통신공학부) ;
  • 김대윤 (충북대학교 정보통신공학부) ;
  • 한지은 (충북대학교 정보통신공학부) ;
  • 육미선 (충북대학교 정보통신공학부) ;
  • 임종태 (충북대학교 정보통신공학부) ;
  • 복경수 (충북대학교 정보통신공학부) ;
  • 유재수 (충북대학교 정보통신공학부)
  • Received : 2015.07.23
  • Accepted : 2015.08.05
  • Published : 2015.08.28


Recently, interests in detecting hot topics have been significantly growing as it becomes important to find out and analyze meaningful information from the large amount of data which flows in from social network services. Since it deals with a number of random writings that are not confirmed in advance due to the characteristics of SNS, there is a problem that the reliability of the results declines when hot topics are predicted from the writings. To solve such a problem, this paper proposes a high reliable hot topic prediction scheme considering user influences in social networks. The proposed scheme extracts a set of keywords with hot issues instantly through the modified TF-IDF algorithm based on Twitter. It improves the reliability of the results of hot topic prediction by giving weights of user influences to the tweets. To show the superiority of the proposed scheme, we compare it with the existing scheme through performance evaluation. Our experimental results show that our proposed method has improved precision and recall compared to the existing method.


Social Network Services(SNS);Twitter;Hot Topics;Prediction


Supported by : 정보통신기술진흥센터, 한국연구재단, 한국에너지기술평가원(KETEP)


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