ICWSM 2011 Liveblog: Day One

The 5th Int’l AAAI Conference on Weblogs and Social Media
19-21 July 2011, Barcelona, Spain
Sponsored by the Association for the Advancement of Artificial Intelligence.

The fifth International Conference on Weblogs and Social Media brings together researchers from the disciplines of NLP, Social Psychology, Data Mining, Sociology and Visualization to increase our understanding of social media in all its incarnations. Research that blends social science and technology is especially encouraged.

Vladimir Barash is attending the 2011 ICWSM and reports from the sessions.

These are rough notes from Day One of ICWSM.

Manuel Castells – Keynote. Social Media and Wiki-Revolutions
–social media and social change
–what makes human human = meaningful communication
—changes in the nature of communication process => changes everywhere in society
—-more specifically, changes in the nature of communication process => changes in power relationships

—(mass-self communication) = social media
—-organized by large corporations but driven by desires of communicators (people)
—-this principle is embedded in the technical structure of the internet
—–enterpreneurial character, hacker culture

–culture of autonomy
–individuation != individualism
—referential point for society in what groups of individuals decide is important for them (as opposed to cultural / societal institutions)

–Castells study of internet usage in Catalonia
—empirical test of Internet as a platform of autonomy
—results: top 20% of population ranking high on autonomy according to several personality-based characteristics use the internet the most
—suggest there is a synergistic interaction between autonomy and use of the Internet(?)

–power and counter-power = dynamics of society

Continue reading

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

Continue reading

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)

Continue reading

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

On the robustness of Twitter and false SAT Analogies

This blog entry is a response to  Cody Brown’s post here. I wanted to leave a comment on the post, but it was going to run a bit long, so I thought I’d put up a response of my own.

Cody’s piece is interesting and well-reasoned. The basic argument he makes is that Twitter, much like Myspace, became popular before it new what it was, and is now suffering an identity crisis that will force it to fracture / fade into obscurity and be replaced by more focused applications. The comparison of Twitter to Myspace, however, falls short: in one sentence, I would claim that Twitter will not go the way of Myspace, because Myspace is more of an environment, whereas Twitter is a platform.

It’s true, both Twitter and Myspace suffer from lack of clear vision and perhaps an overabundance of uses. It’s a citizen journalism service, a way to catch up / chat with your friends, a procrastination device, a way for fans to follow celebrities, etc. You can use Twitter to write novels and play chess. This was the problem with Myspace: it offered users unlimited means of self-expression without a single overarching paradigm. When users were bored with expressing themselves (as all users inevitably are), there was nothing solid to keep them on the site, and so they drifted. But Twitter does have a single overarching paradigm: the tweet-stream.

Twitter’s greatest use is as a low-level service to provide individuals with a socially filtered, digestible, flexible stream of information. E-mail doesn’t provide digestible streams: the limit to the length of an e-mail is MUCH bigger than 140 characters. RSS is not socially filtered. Social bookmarking is both digestible and socially filtered, but less flexible – it doesn’t allow users to engage in dialogue and commentary as part of the bookmarking stream. Facebook has profiles and pictures and events which make the stream (news feed) much less digestible. 

Does this mean that Twitter is perfect? Not at all. I think Twitter is going through an identity crisis (though that crisis is going to happen more on the surface and the periphery, and not detract from the utility of the core service). In my opinion, the way out of that crisis lies in going back to the core, to the socially filtered, digestible flexible information stream. There have been a number of apps built on top of Twitter, but, to my knowledge, these apps have yet to fully harness the stream. First step is search, which is happening and is a good thing. Second step should be better filtering – I want real-time manipulation of my tweet-stream to filter out posts by person X. Third step should be extracting social interactions from pure information streams – I want to grab all the @posts I’ve had with X, and their responses, and the responses of all of my other friends who have seen these @posts and commented on them. I want an interactive social graph plugin that I can drag / click on to expose tweets between / by different subsets of my followers, or followees, or both. These features would not only help me manage incoming tweets, but also help me organize my stream, and give me more control over it. 

So these are some thoughts about Twitter, why it’s not going the way of MySpace, and how it could be better. I hope that the features I listed are either a) already available and I don’t know about them, or b) will be developed soon. Twitter is a great platform and has been incredibly useful for my own social media management. I hope to see it grow and improve in the coming months!

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)

Continue reading

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

Continue reading