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 competing incentives

Red, blue. People unaware of global network structure

Payoffs: if everyone picks same color w/in 2 minutes, experiment ends, and everyone gets some payoff. But different players have different incentives (e.g. I may get paid p if everyone converges to blue, but 2p if everyone converges to red). If there is no consensus, nobody gets a payoff

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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. Prediction

Previous work:

Deliberation: Honeycutt and Herring – Twitter not only used for one-way comm, but 31% of all tweets direct a specific addressee. Kroop and Jansen – political internet discussion boards dominated by small # of heavy users

Sentiment: How accurately can Twitter inform us about the electorate’s political sentiment?

Prediction: can Twitter serve as a predictor of the election result?

Data: examined more than 100k tweets and extracted their sentiment using LIWC

Target: German federal election 2009


1. While Twitter is used as a forum for political deliberation on substantive issues, this forum is dominated by heavy users

Two widely accepted indicators of blog-based deliberation:

-The exchange of substantive issues (31% of all messages contain “@”),

-Equality of participaion: While the distribution of users across groups is almost identical with the one found on internet message boards, we find even less equality of participation for the political debate on Twitter. Additional analyses have shown users to exhibit a party-bias in the volume and sentiment of messages.

2. The online sentiment in tweets reflects nuanced offline differences between the politicians in our sample.

LIWC profiles:

-Leading candidates: Very similar profile for all leading candidates, only polarizing political characters, such as liberal leader and socialist, deviate in line with their roles as opposition leaders. Messages mentioning Steinmeir (coalition leader) are most tentative

3. Similarity of profiles is a plausible reflection of the political proximity between the parties

Key findings: high convergence of leading candidates, more divergence among politicians of governin grand coalition than among those of a potential right wing coalition

4. Activity on Twitter prior to election seems to validly reflect the election outcome (MAE 1.65%), and joint party mentions accurately reflect the political ties between parties.

From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series (Brendan O’Connor)

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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

ICWSM 2010 - Bob Kraut
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
-identity based groups
-bond based groups
Added Identity & Bond Features to MovieLens
Introduced Subgroups into MovieLens
Identity features that focus on subgroups
Individual profiles
bond-based design:+11% logins
identity-based design:+44% logins

Call for Papers – ICWSM 2010 – Washington, D.C. May 23-26

Here is the Call for Papers for the

Fourth International AAAI Conference on Weblogs and Social Media (ICWSM-10)
May 23-26, 2010
George Washington University, Washington, DC

Sponsored by the Association for the Advancement of Artificial Intelligence

Tutorial Proposals: December 1, 2009
Paper Submission: January 8, 2010
Poster/Demo Submission: January 8, 2010

Paper Acceptance: March 3, 2010
Poster/Demo Acceptance: March 3, 2010
Workshop Submission: March 1, 2010
Camera Ready Copies: March 12, 2010

Featuring a keynote by:
Professor Bob Kraut
, CMU,
on “Designing Online Communities from Theory

Professor Michael Kearns, Computer and Information Science,
Univ. of Pennsylvania,
on “Behavioral Experiments in Strategic Networks”

Speakers in Special Sessions:
– Nicole Ellison, Dept. of Telecommunication,
Information Studies and Media, Michigan State Univ.
– James Pennebaker, Dept. of Psychology, Univ. of Texas, Austin
– S. Craig Watkins, Dept. of Radio, TV and Film, Univ. of Texas, Austin- Don Burke, CIA Directorate of Science and Technology, Intellipedia
– Haym Hirsh, National Science Foundation IIS Division Director
– Macon Phillips, U.S. White House, Head of New Media

Tutorial Speakers will include:
– Jake Hofman, Yahoo! Research,
“Large-scale social media analytics with Hadoop”

– Cindy Chung and James Pennebaker, Univ. Texas,
“Using LIWC to uncover social psychology in social media”

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ICWSM 2009 – Pictures and Posters

The recent 2009 ICWSM conference featured research into the nature of a wide range of social media.

[flickrset id=”72157618579371124″ thumbnail=”square” overlay=”true” size=”medium”]

Some highlights:
An Examination of Language Use in Online Dating Profiles
Meenakshi Nagarajan, Marti Hearst

Event Detection and Tracking in Social Streams
Hassan Sayyadi, Matthew Hurst, Alexey Maykov

Gephi: An Open Source Software for Exploring and Manipulating Networks
Mathieu Bastian, Sebastian Heymann, Mathieu Jacomy

Information Diffusion in Computer Science Citation Networks
Xiaolin Shi, Belle Tseng, Lada Adamic

Considering the Sources: Comparing Linking Patterns in Usenet and Blogs
Mary McGlohon, Matthew Hurst

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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