[Vladimir Barash is liveblogging the ICWSM conference]
10.30am A categorical model for discovering latent structure in social annotations (Said Kashoob)
Given a collection of web objects, users and tags, can we model the underlying tag generation process?
-Discover implict communities of interest?
-Categories of related tags?
-For given category, id most relevant objs for category
-compare categories
Initial thoughts: content-based topic modeling (Latent Dirichlet Allocation, LSA). Recent work applying LDA models to tags (Wu 2006, Zhou 2008)
[Vladimir Barash is liveblogging the ICWSM conference] 9-10AM: A Tempest: Or, on the Flood of Interest in Sentiment Analysis, Opinion Mining, and the Computational Treatment of Subjective Language (Lillian Lee)
-Sentiment analysis using discussion structure: clasify speeches in US congressional floor debates as supporting or opposing proposed legislation -Individual doc classifier -agreement (degree) classifier for pairs of speeches
-Agreement info allows COLLECTIVE CLASSIFICATION – “agreeing speeches should get the same label”
-ECON: debate about effect of sentiment on sales
-comScore (users willing to pay 20-99% more for 5 star item vs. 4 star item)
-Jury is still out
-SOC: What opinions are influential? (Niculescu-Danescu Muzyl et al.)
-Prior work has focused on features of text and has not been in context of sociological aspects of reviews
-look at helpfulness scores
On Tuesday night Marc Smith and I will be presenting the poster for our paper, "Distinguishing Knowledge vs Social Capital in Social Media with Roles and Context" at the International Conference for Weblogs and Social Media. You can find the…