Ranking news articles based on popularity prediction

Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012

Volumn , Issue , 2012, Pages 106-110

  Tatar, Alexandru ^a   Antoniadis, Panayotis ^a   De Amorim, Marcelo Dias ^a   Fdida, Serge ^a  

^a UNIVERSITÉ PIERRE ET MARIE CURIE   (France)

Author keywords

News articles; Popularity; Prediction; Ranking

Indexed keywords

CACHING STRATEGY; CONTENT POPULARITIES; INTERNET USERS; LINEAR PREDICTION METHOD; MOBILE USERS; NEWS ARTICLES; ON-LINE CONTENTS; ONLINE ADVERTISEMENTS; ONLINE NEWS; POPULARITY; POPULARITY PREDICTIONS; PREDICTION METHODS; PREDICTION MODEL; PREDICTION TASKS; RANKING; RANKING PERFORMANCE; RANKING PROBLEMS; USER ATTENTION;

GLOBAL SYSTEM FOR MOBILE COMMUNICATIONS; SOCIAL NETWORKING (ONLINE);

FORECASTING;

EID: 84874248406     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ASONAM.2012.28     Document Type: Conference Paper

References (16)

1. G. Szabo and B. A. Huberman, "Predicting the popularity of online content, " Communications of the ACM, vol. 53, no. 8, p. 80, 2008.
2. M. Tsagkias, W. Weerkamp, and M. De Rijke, "News comments: Exploring, modeling, and online prediction, " in Proceedings of the 32nd European conference on Advances in Information Retrieval, ser. ECIR2010. Springer, 2010.
3. J. Lee, S. Moon, and K. Salamatian, "An approach to model and predict the popularity of online contents with explanatory factors, " in Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01. IEEE Computer Society, 2010.
4. K. Lerman and T. Hogg, "Using a model of social dynamics to predict popularity of news, " in Proceedings of the 19th international conference on World wide web, ser. WWW '10. New York, NY, USA: ACM, 2010, pp. 621-630.
5. F. Wu and B. Huberman, "Novelty and collective attention, " Proceedings of the National Academy of Sciences, vol. 104, no. 45, p. 17599, 2007.
6. M. Simkin and V. Roychowdhury, "Why does attention to web articles fall with time?" Arxiv preprint arXiv:1202.3492, 2012.
7. M. Cha, H. Kwak, P. Rodriguez, Y. Ahn, and S. Moon, "I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system, " in Proceedings of the 7th ACM SIGCOMM conference on Internet measurement. ACM, 2007, pp. 1-14.
8. P. Van Mieghem, N. Blenn, and C. Doerr, "Lognormal distribution in the digg online social network, " Eur. Phys. J. B, vol. 83, pp. 251-261, 2011.
9. A. Clauset, C. Shalizi, and M. Newman, "Power-law distributions in empirical data, " SIAM Rev., vol. 51, pp. 661-703, November 2009.
10. D. Easley and J. Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Cambridge University Press, 2010.
11. A. Tatar, P. Antoniadis, A. Limbourg, M. D. de Amorim, J. Leguay, and S. Fdida, "Predicting the popularity of online articles based on user comments, " in WIMS'11. ACM, 2011, pp. 67-75.
12. C. D. Manning, P. Raghavan, and H. Schtze, Introduction to Information Retrieval. New York, NY, USA: Cambridge University Press, 2008.
13. A. Kaltenbrunner, V. Gomez, and V. Lopez, "Description and prediction of slashdot activity, " in Proceedings of the 2007 Latin American Web Conference. Washington, DC, USA: IEEE Computer Society, 2007, pp. 57-66.
14. R. Bandari, S. Asur, and B. Huberman, "The pulse of news in social media: Forecasting popularity, " Arxiv preprint arXiv:1202.0332, 2012.
15. C. Hsu, E. Khabiri, and J. Caverlee, "Ranking comments on the social web, " in Computational Science and Engineering, 2009. CSE'09. International Conference on, vol. 4. IEEE, 2009, pp. 90-97.
16. P. Yin, P. Luo, M. Wang, and W.-C. Lee, "A straw shows which way the wind blows: ranking potentially popular items from early votes, " in Proceedings of the fifth ACM international conference on Web search and data mining, ser. WSDM '12. ACM, 2012, pp. 623-632.