On the prediction of re-tweeting activities in social networks - A report on WISE 2012 challenge

Sayan Unankard*, Ling Chen, Peng Li, Sen Wang, Zi Huang, Mohamed A. Sharaf, Xue Li

*此作品的通信作者

研究成果: Conference contribution同行評審

5 引文 斯高帕斯(Scopus)

摘要

This paper reports on our participation in the Data Mining track of the WISE 2012 Challenge. The challenge is to predict the volume of future re-tweets and possible views for 33 given original short messages (tweets). Towards this, we compare and contrast four different methods and highlight our methods of choice for accomplishing this challenge. The first method is a naïve approach that discovers a regression function based on the popularity of messages and network connectivity. The second approach is to build a classifier that learns a classification model based on the user's preferences in different categories of topics. The third approach focuses on a network simulation that leverages a Monte Carlo method to simulate re-tweeting paths starting from a root message. The fourth approach uses collaborative filtering to build a recommendation model. The results of these four methods are compared in terms of their effectiveness and efficiency. Finally, insights into predicting message spreading in social networks are also given.

原文English
主出版物標題Web Information Systems Engineering, WISE 2012 - 13th International Conference, Proceedings
頁面744-754
頁數11
DOIs
出版狀態Published - 2012
事件13th International Conference on Web Information Systems Engineering, WISE 2012 - Paphos, Cyprus
持續時間: 28 11月 201230 11月 2012

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7651 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference13th International Conference on Web Information Systems Engineering, WISE 2012
國家/地區Cyprus
城市Paphos
期間28/11/1230/11/12

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