Toward precise user-topic alignment in online social media

Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015

Volumn , Issue , 2015, Pages 767-775

  Xu, Jiejun ^a   Lu, Tsai Ching ^a  

^a Hughes Aircraft Co   (United States)

Author keywords

bi relational graph; multi label learning; online social media; Twitter; user topic modeling

Indexed keywords

DATA MINING; GRAPH THEORY; LEARNING SYSTEMS; SOCIAL NETWORKING (ONLINE);

MULTI-LABEL LEARNING; ONLINE SOCIAL MEDIAS; RELATIONAL GRAPH; TOPIC MODELING; TWITTER;

BIG DATA;

EID: 84963727701     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BigData.2015.7363821     Document Type: Conference Paper

References (30)

1. D. Ahn, T. Kim, S. J. Hyun, and D. Lee. Inferring user interest using familiarity and topic similarity with social neighbors in facebook. In Web Intelligence, 2012.
2. P. Bhattacharya, M. B. Zafar, N. Ganguly, S. Ghosh, and K. P. Gummadi. Inferring user interests in the twitter social network. In Proceedings of the 8th ACM Conference on Recommender Systems (RecSys), New York, NY, USA, 2014.
3. V. Blondel, J. Guillaume, R. Lambiotte, and E. Mech. Fast unfolding of communities in large networks. J. Stat. Mech, page P10008, 2008.
4. J. Bu, S. Tan, C. Chen, C. Wang, H. Wu, L. Zhang, and X. He. Music recommendation by unified hypergraph: Combining social media information and music content. In International Conference on Multimedia (MM), 2010.
5. R. Compton, D. Jurgens, and D. Allen. Geotagging one hundred million twitter accounts with total variation minimization. In IEEE International Conference on Big Data, volume abs/1404. 7152, 2014.
6. J. Q. Jiang. Learning protein functions from bi-relational graph of proteins and function annotations. In WABI, Lecture Notes in Computer Science, 2011.
7. P. Kapanipathi, P. Jain, C. Venkataramani, and A. Sheth. User interests identification on twitter using a hierarchical knowledge base. In V. Presutti, C. dAmato, F. Gandon, M. dAquin, S. Staab, and A. Tordai, editors, The Semantic Web: Trends and Challenges, volume 8465 of Lecture Notes in Computer Science, pages 99-113. Springer International Publishing, 2014.
8. H. Kwak, C. Lee, H. Park, and S. Moon. What is twitter, a social network or a news media? In Proceedings of the 19th International Conference on World Wide Web, WWW '10, pages 591-600, New York, NY, USA, 2010. ACM.
9. W.-Y. Lee, L.-C. Hsieh, G.-L. Wu, and W. Hsu. Graph-based semi-supervised learning with multi-modality propagation for large-scale image datasets. J. Vis. Comun. Image Represent., 24 (3), Apr. 2013.
10. Y. Liu, C. Kliman-Silver, and A. Mislove. The tweets they are a-changin: Evolution of twitter users and behavior. In E. Adar, P. Resnick, M. D. Choudhury, B. Hogan, and A. Oh, editors, ICWSM. The AAAI Press, 2014.
11. G. Lotan, E. Graeff, M. Ananny, D. Gaffney, I. Pearce, and danah boyd. The arab spring- the revolutions were tweeted: Information flows during the 2011 tunisian and egyptian revolutions. International Journal of Communication, 5 (0), 2011.
12. H. Ma, D. Zhou, C. Liu, M. R. Lyu, and I. King. Recommender systems with social regularization. In Proceedings of the Fourth ACM International Conference on Web Search and Data Mining (WSDM), 2011.
13. M. Michelson and S. A. Macskassy. Discovering users' topics of interest on twitter: A first look. In Proceedings of the Fourth Workshop on Analytics for Noisy Unstructured Text Data. ACM, 2010.
14. A. Mislove, B. Viswanath, K. P. Gummadi, and P. Druschel. You are who you know: Inferring user profiles in online social networks. In Proceedings of the Third ACM International Conference on Web Search and Data Mining, WSDM '10, pages 251-260, New York, NY, USA, 2010. ACM.
15. R. Ottoni, D. B. L. Casas, J. P. Pesce, W. M. Jr., C. Wilson, A. Mislove, and V. Almeida. Of pins and tweets: Investigating how users behave across image-and text-based social networks. In Proceedings of the Eighth International Conference on Weblogs and Social Media (ICWSM), 2014.
16. D. Ramage, D. Hall, R. Nallapati, and C. D. Manning. Labeled lda: A supervised topic model for credit attribution in multi-labeled corpora. In Conference on Empirical Methods in Natural Language Processing (EMNLP), 2009.
17. N. K. Sharma, S. Ghosh, F. Benevenuto, N. Ganguly, and K. Gummadi. Inferring who-is-who in the twitter social network. In Proceedings of the 2012 ACM Workshop on Workshop on Online Social Networks, WOSN '12, pages 55-60, New York, NY, USA, 2012. ACM.
18. W. Shen, J. Wang, P. Luo, and M. Wang. Linking named entities in tweets with knowledge base via user interest modeling. In Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD), 2013.
19. G. Tian and L. Jing. Recommending scientific articles using bi-relational graph-based iterative rwr. In Proceedings of the 7th ACM Conference on Recommender Systems (RecSys), New York, NY, USA, 2013. ACM.
20. J. Wang, W. X. Zhao, Y. He, and X. Li. Infer user interests via link structure regularization. ACM Trans. Intell. Syst. Technol., 5 (2):23:1-23:22, Apr. 2014.
21. T. Wang, H. Liu, J. He, and X. Du. Mining user interests from information sharing behaviors in social media. In J. Pei, V. Tseng, L. Cao, H. Motoda, and G. Xu, editors, Advances in Knowledge Discovery and Data Mining, volume 7819 of Lecture Notes in Computer Science, pages 85-98. Springer Berlin Heidelberg, 2013.
22. Z. Wen and C.-Y. Lin. On the quality of inferring interests from social neighbors. In Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD), 2010.
23. J. Weng, E.-P. Lim, J. Jiang, and Q. He. Twitterrank: finding topic-sensitive influential twitterers. In ACM International Conference on Web Search and Data Mining (WSDM), 2010.
24. L. Weng and F. Menczer. Topicality and impact in social media: Diverse messages, focused messengers. PLoS ONE, 10 (2):e0118410, 02 2015.
25. J. Xu, R. Compton, T.-C. Lu, and D. Allen. Rolling through tumblr: Characterizing behavioral patterns of the microblogging platform. In ACM Web Science, 2014.
26. J. Xu and T.-C. Lu. Inferring user interests on tumblr. In Social Computing, Behavioral-Cultural Modeling, and Prediction, volume 9021 of Lecture Notes in Computer Science, pages 458-463. Springer International Publishing, 2015.
27. Y. Yamaguchi, T. Amagasa, and H. Kitagawa. Tag-based user topic discovery using twitter lists. In International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Kaohsiung, Taiwan, 25-27 July 2011.
28. G. Yu, C. Domeniconi, H. Rangwala, G. Zhang, and Z. Yu. Transductive multi-label ensemble classification for protein function prediction. In International Conference on Knowledge Discovery and Data Mining (KDD), New York, NY, USA, 2012.
29. D. Zhou, O. Bousquet, T. N. Lal, J. Weston, and B. Schlkopf. Learning with local and global consistency. In NIPS. MIT Press, 2004.
30. X. Zhu. Semi-supervised learning literature survey. In University of Wisconsin Madison, Computer Sciences TR-1530, 2008.