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 :
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