DocumentCode
683953
Title
Iterative algorithm for retweeting prediction in Twitter
Author
Li, Yingle ; Wu, Zhen ; Yu, Hongtao ; Liu, Lixiong
Author_Institution
National Digital Switching System Engineering & Technological R&D Center, Zhengzhou 450002, Henan, China
fYear
2013
fDate
23-25 March 2013
Firstpage
541
Lastpage
545
Abstract
Twitter is emerging social media. There is an important practical significance to study its communication effect in many aspects of the Marketing Management, Public Sentiment, Hot Extraction and so on. The retweeting scale is an important indicator to reflect the communication effect. Based on analyzing the factors, a prediction algorithm based on SVM was proposed for retweeting with five features: publisher influence, acceptor activity, interest level, content importance and intimacy. Furthermore, the prediction algorithm for retweeting scale was proposed based above, the method to evaluate the prediction accuracy was given. At last the experiment with Twitter data showed a good result that the prediction accuracy of retweeting scale was up to 86.63%.
Keywords
Accuracy; Classification algorithms; Feature extraction; Media; Prediction algorithms; Support vector machines; Twitter;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Technology (ICIST), 2013 International Conference on
Conference_Location
Yangzhou
Print_ISBN
978-1-4673-5137-9
Type
conf
DOI
10.1109/ICIST.2013.6747607
Filename
6747607
Link To Document