You are where you go: Inferring demographic attributes from location check-ins

WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining

Volumn , Issue , 2015, Pages 295-304

  Zhong, Yuan ^a,b   Yuan, Nicholas Jing ^a   Zhong, Wen ^a,c   Zhang, Fuzheng ^a,d   Xie, Xing ^a  

^a MICROSOFT RESEARCH   (United States)

^b NORTHEASTERN UNIVERSITY   (United States)

^c STONY BROOK UNIVERSITY   (United States)

^d UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Demographics; Location knowledge; Prediction; Spatiality; Temporality; Tensor facotorization

Indexed keywords

FORECASTING; LARGE DATASET; LOCATION; POPULATION STATISTICS; PREDICTIVE ANALYTICS; SEMANTICS; SOCIAL NETWORKING (ONLINE); TENSORS;

DEMOGRAPHICS; HETEROGENEOUS DOMAINS; LOW-DIMENSIONAL REPRESENTATION; ON-LINE SOCIAL NETWORKS; ONLINE CUSTOMER REVIEWS; SPATIALITY; TEMPORALITY; TENSOR FACTORIZATION;

DATA MINING;

EID: 84928711137     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2684822.2685287     Document Type: Conference Paper

References (33)

1. E. Acar, S. A. Camtepe, M. S. Krishnamoorthy, and B. Yener. Modeling and multiway analysis of chatroom tensors. In Intelligence and Security Informatics, pages 256-268. Springer, 2005.
2. E. Acar, D. M. Dunlavy, and T. G. Kolda. Link prediction on evolving data using matrix and tensor factorizations. In Data Mining Workshops, 2009. ICDMW'09. IEEE International Conference on, pages 262-269. IEEE, 2009.
3. M. D. Back, S. C. Schmukle, and B. Egloff. How extraverted is honey. bunny77@ hotmail. de? inferring personality from e-mail addresses. Journal of Research in Personality, 42(4): 1116-1122, 2008.
4. B. W. Bader, M. W. Berry, and M. Browne. Discussion tracking in enron email using parafac. In Survey of Text Mining II, pages 147-163. Springer, 2008.
5. rd Annual Meeting on Association for Computational Linguistics, pages 435-442. Association for Computational Linguistics, 2005.
6. S. Brdar, D. Culibrk, and V. Crnojevic. Demographic attributes prediction on the real-world mobile data. In Proc. Mobile Data Challenge by Nokia Workshop, in Conjunction with Int. Conf. on Pervasive Computing, Newcastle, UK, 2012.
7. X. Cao, G. Cong, and C. S. Jensen. Mining significant semantic locations from gps data. Proceedings of the VLDB Endowment, 3(1-2):1009-1020, 2010.
8. P. T. Costa Jr and R. R. McCrae. Reply to ben-porath and waller. Psychological Assessment, 4(1):20-22, 1992.
9. G. De'Ath. Boosted trees for ecological modeling and prediction. Ecology, 88(1):243-251, 2007.
10. Y. Dong, Y. Yang, J. Tang, and N. V. Chawla. Inferring user demographics and social strategies in mobile social networks. 2014.
11. L. A. Fast and D. C. Funder. Personality as manifest in word use: correlations with self-report, acquaintance report, and behavior. Journal of personality and social psychology, 94 (2):334, 2008.
12. M. C. Gonzalez, C. A. Hidalgo, and A.-L. Barabasi. Understanding individual human mobility patterns. Nature, 453(7196):779-782, 2008.
13. M. Kosinski, D. Stillwell, and T. Graepel. Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15):5802-5805, 2013.
14. W. Labov. The social stratification of English in New York City. PhD thesis, Columbia university., 1964.
15. J. Liu, O. Wolfson, and H. Yin. Extracting semantic location from outdoor positioning systems. In MDM, page 73, 2006.
16. 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, pages 251-260. ACM, 2010.
17. F. Mosteller and D. L. Wallace. Inference in an authorship problem: A comparative study of discrimination methods applied to the authorship of the disputed federalist papers. Journal of the American Statistical Association, 58(302): 275-309, 1963.
18. D. Murray and K. Durrell. Inferring demographic attributes of anonymous internet users. In Web Usage Analysis and User Profiling, pages 7-20. Springer, 2000.
19. G. Ou and Y. L. Murphey. Multi-class pattern classification using neural networks. Pattern Recognition, 40(1):4-18, 2007.
20. th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 430-438. ACM, 2011.
21. S. Pradhan. Semantic location. Personal Technologies, 4(4): 213-216, 2000.
22. th SIGSPATIAL international conference on advances in geographic information systems, pages 53-60. ACM, 2010.
23. nd international workshop on Search and mining user-generated contents, pages 37-44. ACM, 2010.
24. L. Rokach. Ensemble-based classifiers. Artificial Intelligence Review, 33(1-2):1-39, 2010.
25. P. Symeonidis, A. Nanopoulos, and Y. Manolopoulos. A unified framework for providing recommendations in social tagging systems based on ternary semantic analysis. Knowledge and Data Engineering, IEEE Transactions on, 22 (2):179-192, 2010.
26. P. Trudgill. The social differentiation of English in Norwich, volume 13. CUP Archive, 1974.
27. th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 618-626. ACM, 2011.
28. Q. Wu, C. J. Burges, K. M. Svore, and J. Gao. Adapting boosting for information retrieval measures. Information Retrieval, 13(3):254-270, 2010.
29. th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pages 102-111. ACM, 2011.
30. th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 520-528. ACM, 2011.
31. th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 186-194. ACM, 2012.
32. N. J. Yuan, F. Zhang, D. Lian, K. Zheng, S. Yu, and X. Xie. We know how you live: exploring the spectrum of urban lifestyles. In Proceedings of the first ACM conference on Online social networks, pages 3-14. ACM, 2013.
33. th international conference on World wide web, pages 531-540. ACM, 2009.