Earticle

초록

영어

Twitter that represents the social network makes it available to retweet the tweet that other users have written without restriction. Therefore, information can be conveniently delivered on a real-time basis. Thanks to such an advantage, studies that utilize twitter are recently being developed. This paper is intended to establish data base based on BBC News Twitter on a daily basis making a daily tweet as a token according to gap and moving to a phase of reprocessing that removes the stopwords. Each word that is created and retweeted after a phase of reprocessing is applied to calculate the total added retweet value, dividing them by the number of daily average retweet to derive topic weight value. This procedure is called ‘Topic Weight Measurement.’ This way, the topics are extracted. After analyzing the pattern according to the date, topics that are extracted using proposed procedures are compared with frequency pattern that are provided by Google Trends. As a result, it was confirmed that topics provided by BBC News Twitter is similar with word searching pattern graph of Google Trends

목차

Abstract
 1. Introduction
 2. Related Works
 3. A Method for Measuring Topic Weight in News Twitter
 4. Pattern Analysis of Twitter Topics
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Jeongin Kim [ Dept. of Computer Engineering, Chosun University ]
• Byeongkyu Ko [ Dept. of Computer Engineering, Chosun University ]
• Huijin Jeong [ Dept. of Computer Engineering, Chosun University ]
• Pankoo Kim [ Dept. of Computer Engineering, Chosun University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605