ICML '06 Proceedings of the 23rd international conference on Machine learning
Finding frequent items in data streams
Proceedings of the VLDB Endowment
Advertiser-centric approach to understand user click behavior in sponsored search
Proceedings of the 20th ACM international conference on Information and knowledge management
SES: Sentiment Elicitation System for Social Media Data
ICDMW '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining Workshops
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Social media websites are currently central hubs on the Internet. Major online social media platforms are not only places for individual users to socialize but are increasingly more important as channels for companies to advertise, public figures to engage, etc. In order to optimize such advertising and engaging efforts, there is an emerging challenge for knowledge discovery on today's Internet. The goal of knowledge discovery is to understand the entire online social landscape instead of merely summarizing the statistics. To answer this challenge, we have created VOXSUP as a unified social engagement framework. Unlike most existing tools, VOXSUP not only aggregates and filters social data from the Internet, but also provides what we call Voxsupian Knowledge Discovery (VKD). VKD consists of an almost human-level understanding of social conversations at any level of granularity from a single comment sentiment to multi-lingual inter-platform user demographics. Here we describe the technologies that are crucial to VKD, and subsequently go beyond experimental verification and present case studies from our live VOXSUP system.