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Why we search: Visualizing and predicting user behavior
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Banff, Alberta, Canada, ACM
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E. ADAR, D. S. WELD, B. N. BERSHAD, et al. (2007). Why we search: visualizing and predicting user behavior. Proceedings of the 16th international conference on World Wide Web. Banff, Alberta, Canada, ACM: 161-170.
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Can blog communication dynamics be correlated with stock market activity?
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Pittsburgh, PA, USA, ACM
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M. D. CHOUDHURY, H. SUNDARAM, A. JOHN, et al. (2008). Can blog communication dynamics be correlated with stock market activity? Proceedings of the nineteenth ACM conference on Hypertext and hypermedia. Pittsburgh, PA, USA, ACM: 55-60.
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Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia
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Visualizing tags over time
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Edinburgh, Scotland, ACM
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M. DUBINKO, R. KUMAR, J. MAGNANI, et al. (2006). Visualizing tags over time. Proceedings of the 15th international conference on World Wide Web. Edinburgh, Scotland, ACM: 193-202.
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The predictive power of online chatter
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Proceeding of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining Chicago
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Mining multi-faceted overviews of arbitrary topics in a text collection
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ARSA: A sentiment-aware model for predicting sales performance using blogs
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Amsterdam, The Netherlands, ACM
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Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
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A probabilistic approach to spatiotemporal theme pattern mining on weblogs
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Edinburgh, Scotland, ACM
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Q. MEI, C. LIU, H. SU, et al. (2006). A probabilistic approach to spatiotemporal theme pattern mining on weblogs. Proceedings of the 15th international conference on World Wide Web. Edinburgh, Scotland, ACM: 533-542.
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Topic modeling with network regularization
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Beijing, China, ACM
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Q. MEI, D. CAI, D. ZHANG, et al. (2008). Topic modeling with network regularization. Proceeding of the 17th international conference on World Wide Web. Beijing, China, ACM: 101-110.
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Proceeding of the 17th International Conference on World Wide Web
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Predicting the tendency of topic discussion on the online social networks using a dynamic probability model
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Pittsburgh, PA, USA, ACM
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Y. ZHOU, X. GUAN, Z. ZHANG, et al. (2008). Predicting the tendency of topic discussion on the online social networks using a dynamic probability model. Proceedings of the hypertext 2008 workshop on Collaboration and collective intelligence. Pittsburgh, PA, USA, ACM: 7-11.
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