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ICWSM 2010 Liveblog, Day 3

Fourth International AAAI Conference on Weblogs and Social Media (ICWSM-10) Michael Kearns Keynote Experiments: Graph Coloring / Consensus / Voting Topology of the Network vs. what was the network used for? Voting experiments – similar to consensus, with a crucial strategic difference. Introduce a tension between: -Individual preferences -Collective unity -Color choices; challenge comes from [...]
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ICWSM 2010 Liveblog, Day 2

Fourth International AAAI Conference on Weblogs and Social Media (ICWSM-10) ***Microblogging 2*** Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment (Tumasjan et al.) Successful use of social media in las presidential campaign has established twitter as an integral part of political campaign toolbox Goal: analyze on Twitter: 1. Deliberation, 2. Sentiment, 3. [...]
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ICWSM 2010 Liveblog, Day 1

Fourth International AAAI Conference on Weblogs and Social Media (ICWSM-10) We will be liveblogging (when possible) from ICWSM 2010, going on now! Keynote: Bob Kraut, CMU implications for community design -offline theories of socialization helpful, not definitive -online communities can build in good socialization practice -e.g. WP welcoming committee Two Types of Commitments to Groups [...]
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Liveblogging ICWSM 2009 – Day 2

ICWSM 2009 in San Jose

[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)

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Liveblogging ICWSM 2009 – Day 1

2009 ICWSM in San Jose

[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

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