Library and Information Service >
Research on Lifecycle of Microblog
Received date: 2013-12-10
Revised date: 2013-12-21
Online published: 2014-01-05
As a kind of information resource in new environment, the mass data produced by Microblog has its lifespan. Based on the study of three hot topics from Microblog, the amount of comments is considered as the characteristic parameter of Microblog message's lifecycle. The study analyzes the features and distribution of Microblog message's lifecycle and its half-life. The types of Microblog message's life cycle include negative exponent, flat, burst andzigzag. The Microblog doesn't have a fixed half-life and its activity is irrelevant to its lifespan type.
Key words: Microblog; life cycle; lifespan; half-life; comment count
Liu Xiaojuan , Wang Haoxian , Zhang Aiyun . Research on Lifecycle of Microblog[J]. Library and Information Service, 2014 , 58(01) : 72 -78,100 . DOI: 10.13266/j.issn.0252-3116.2014.01.010
[1] Lardinois F. The short lifespan of a tweet: Retweets only happen within the first hour[EB/OL].[2013-11-20]. http://readwrite.com/2010/09/29/the_short_lifespan_of_a_tweet_retweets_only_happen#awesm=~onHN0dzZd0FEm7.
[2] Zaman T, Fox E B, Bradlow E T.A Bayesian approach for predicting the popularity of tweets[OL].[2013-11-20]. http://arxiv.org/pdf/1304.6777v1.pdf.
[3] Barbagallo D, Bruni L, Francalanci C, et al. An empirical study on the relationship between Twitter sentiment and influence in the tourism domain[C]//Proceedings of 19th eTourism Community Conference. New York:Springer, 2012:506-516.
[4] Yang Zi, Guo Jingyi, Cai Keke, et al.Understanding retweeting behaviors in social networks[C]//Proceedings of the 19th ACM International Conference on Information and Knowledge Management.New York: ACM, 2010: 1633-1636.
[5] Kong Shoubin, Feng Ling, Sun Guozheng. Predicting lifespans of popular tweets in Microblog[C]//Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM, 2012:1129-1130.
[6] Naveed N, Gottron T, Kunegis J, et al. Bad news travel fast:A content-based analysis of interestingness on Twitter[C]//Proceedings of the ACM WebSci'11. New York:ACM, 2011:1-7.
[7] Spiro E, Dubois C, Butts C. Waiting for a retweet: Modeling waiting times in information propagation[EB/OL].[2013-12-02]. http://snap.stanford.edu/social2012/papers/spiro-dubois-butts.pdf.
[8] Zhao Xun, Zhu Feida, Qian Weining, et al. Impact of multimedia in Sina weibo: Popularity and life span[C]//Semantic Web and Web Science. New York:Springer, 2013: 55-65.
[9] Jenders M, Kasneci G, Naumann F. Analyzing and predicting viral tweets[C]//The 22nd International Conference on World Wide Web Companion. Geneva: International World Wide Web Conferences Steering Committee, 2013:657-664.
[10] Price D J. Network of Science Papers[J]. Science, 1965, 149(3683): 510-515.
[11] Gosnell C F. Obsolescence of books in college libraries[J].College and Research Libraries, 1944, 5(2):115-125.
[12] 邱均平.信息计量学[M].武汉:武汉大学出版社, 2007.
/
〈 |
|
〉 |