University of Cambridge > > Microsoft Research Cambridge, public talks > Social Media Predictive Analytics: Methods and Applications

Social Media Predictive Analytics: Methods and Applications

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Microsoft Research Cambridge Talks Admins.

This event may be recorded and made available internally or externally via Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending

Large-scale real-time social media analytics provides a novel set of conditions for the construction of predictive models. With individual users as training and test instances, their associated content (“lexical features”) and context (“network features”) are made available incrementally over time, as they converse over discussion forums. We propose various approaches to handling this dynamic data for predicting latent user properties, from traditional batch training and testing, to incremental bootstrapping, and then active learning via interactive rationale crowdsourcing.

We also study the relationships between a variety of predicted user properties, opinions and emotions on a large sample of users in online social network. We first correlate user demographics and personality with the emotional profile emanating from user tweets. We then analyze the relationships between predicted user properties and user-environment emotional contrast estimated over various neighborhoods including friends, retweeted and mentioned users. Finally, we analyze and compare predictive power of latent user properties, emotions and interests for automatically inferring showing off and self-promoting behaviors projected in online social networks.

This talk is part of the Microsoft Research Cambridge, public talks series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


© 2006-2024, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity