Just wanted to share a quick pointer to the First International Workshop on Modeling, Mining and Managing Evolving Social Networks (M3SN) to be co-located with IEEE ICDE 2009 in Shanghai. Following is the CFP via Christian König
The organizers of CIKM 2008 Workshop on Search in Social Media have extended their paper submission deadline from July 20, 2008 to July 27, 2008. For more information please visit the homepage of the workshop. Below is an excerpt from the CFP:
Social applications are the fastest growing segment of the web. Social media are a fascinating phenomenon because they establish new forums for content creation, allow people to connect to each other and share information, and permit novel applications at the intersection of people and information. However, whereas in the general web search is a critical application that drives usability, social media has been primarily popular for connecting people, not for finding information. While there has been progress on searching particular kinds of social media, such as blogs, search in others (facebook/myspace/flickr) are not as well understood. The purpose of this workshop is to focus the attention of the research community on this emerging topic, and to bring together information retrieval and social media researchers to consider the following questions: How should we search in social media? What are the needs of users, and models of those needs, specific to social media search? What models make the most sense? How does search interact with existing uses of social media? What works and what doesn't?
This workshop is chaired by
Note that the event has been updated in the Social Media Calendar as well. To keep track of social media research conferences and venues please subscribe via the calendar.
As I had promised before, I plan to maintain a calendar of social media events. You can subscribe to the calendar here:
I will be on the lookout for events, conferences, workshops and talks that might be of interest to the community. I will try to balance both academic and business/networking event opportunities -- although the primary focus would be research conferences. Please forward me relevant postings and announcements at akshayjava on Gmail. Looking forward to meeting you at the next conference/venue!
BTW, Here is a nice layout of the events using this cool Yahoo Pipe by Tony Hirst: (aaargh! Typepad! you are killing me with this new editor -- the map shows up in the preview but not on my post -- huh!)
SocialDevCamp totally rokced! The event was best described as:
SocialDevCamp East is the Unconference for Thought Leaders of the Future Social Web
Where is the social web going? It's going mobile, to geocentric services, and to open platforms. Join a community of like minded developers, social media gurus and thought leaders for an unconference to discuss the future of the social web.
Here is my trip report from this event:
Those who did not make it really missed out on a great event. But fret no more. Soon there will be an announcement for the SocialDevCamp being held in the Fall -- no excuses that time!
A special thanks to the organizers and sponsors for supporting this event and bringing us all together. (Blogs covering this event)
I am excited about the local BarCamp event organized by David Troy of Twittervision and Ann Bernard, Keith Casey from WhyGoSolo. It looks like a fun event and a great "UnConference" for local entrepreneurs, social media enthusiasts and researchers to get together and talk about the future, innovation of Social Media and the Web.
It promises to be an event that would
bring together forward thinkers – developers, social media gurus, bizdev types – to discuss and Chart the Next Course.
The Agenda and signup details are available on the PBWiki site. Some of the proposed session topics (From the Wiki):
- Mobile Application Development with iPhone & Android
- What are the implications of Geo-based web applications?
- How will Agile Development practices affect ideation and funding processes?
- Platforms Present & Future
- What will matter on the web a year or two from now?
- Where will information aggregation take us?
- Social Media is here to stay – so where will it go next?
- How will Google keep affecting development, the web and our lives?
- What are the next things web users will want from the web?
- What will be the impact of future generations to the current web we know today?
- Social Media in the workplace vs. in life
- How the Web is being broken apart into pieces - Justin Thorp
Fantastic! Cant wait to be there!
There are also some sponsorship opportunities (starting @ $250) available for this event. Also please note that there is no cost for participants (which is great for grad students like me!). :-D
For more details please contact Dave Troy or come and chat with us on Facebook.
Using SentiWordNet for Multilingual Sentiment Analysis
Kerstin Denecke
Subjectivity Analysis is about identifying a set of opinions emotions and thoughts that are expressed in text. As opposed to factual statements (objective text), the goal is to identify if there are any:
The question addressed in this paper is how to analyze subjectivity and sentiments in in multilingual datasets. This was a really well motivated paper and a it was great to hear this talk especially after attending the recent tutorial by Dr. Jan Weibe at ICWSM. One motivation is that a company that sells products in many different countries might want to know the sentiments of its clients. A big difficulty in aggregating across different geographies is analyzing multilingual text.
Some of the difficulties in dealing with multilingual sentiment analysis are:
The solution proposed by Kerstin in this paper is to rely on resources available in English and use existing training sets (from English text) to identify the subjectivity in foreign language text. This is such a simple and effective idea that my first reaction was that of surprise! I am amazed that someone had not proposed it yet!
Kerstin's approach is to take the documents and translate them to English and sentiment analysis is applied on the translated version of the document to determine the polarity. One key technology being used in this work is SentiWordNet. It is a lexical resource for opinion mining that was manually created. It offers a triple of polarity scores for each wordnet synset (pos, neg, objectivity). This is an amazing resource for anyone working on Sentiment analysis. I was unaware of SentiWordNet when we were working on the TREC Blog track 2006. In retrospect, I wish I knew of it back then.
Working with the translated text, this paper identifies each word+POS and does a lookup in sentiword to obtain the scores per synset. Next, they calculate the score for each word class (adj,noun, verbs) for a given document. Finally, the score triples are averaged across the words in the sentences. The document is given a polarity score using the triples across all the sentences.
To identify the polarity there were two approaches that were used:
Evaluation was done by using IMDB archive (1000 pos,neg reviews in English) and the testset was MPQA (English) and Amazon movie reviews (German).
Some sources of errors mentioned in the presentation:
Their results indicate that ML based approach is better and obtains an accuracy of around .65.
Monitoring the evolution of interests in the blogosphere
Iraklis Varlamis (Presenter), Vasilis Vassalos, Antonis Palaios
The authors present a simple (perhaps even obvious) hypothesis that "Interests of bloggers converge around real world events".
A prototype system was built to to analyze blogs and monitor the evolution of interests. Existing search engines monitor the term popularity of words in isolation and the related terms are not clustered in any way to identify the topics. A motivating example presented was around the football world cup season, where there might be terms like "football" "round" "final" "result" "world cup" and aggregated scores for topic would be helpful rather than having to find/view the histograms for each of these terms. Also one can not know all the terms for a given topic. In many cases, multilingual content and difference in vocabulary can further make it difficult to just monitor the term popularity. Other approaches require training a topic based on a given set of training/pre-annotated document pool. This is an expensive and a semi-supervised method can be strongly effected by the selection of the initial document pool.
The goal of their paper is to build an unsupervised approach to cluster the documents and identify the evolution of interest. However, the current algorithm presented is not incremental; but they claim some recent work on an incremental version. The current version of their algorithm uses the DBScan clustering technique. Term space is clustered at the post level and their evaluation is done using inter cluster, intra cluster similarity and the utility function. They have used the BuzzMetrics dataset, however they only focus on blogs that have a post everyday, which brings the dataset down to 2500 blogs. The posts are classified into topics and then the blogs are clustered. The categories are determined by using the Cyberfiber news groups to find the topics and training documents. This is an interesting dataset that I was not aware of.
Some questions that came up were the choice of using newswire documents to learn classifiers, and also the accuracy of the classifiers. While the original hypothesis seems obvious, it can be seen as a litmus test for the efficacy of the clustering algorithms. In particular the examples presented were using the "London Bombing" Event. Any clustering algorithm that groups the related terms must at the very least pass the litmus test to show that it works.
I think that in general there are perhaps two types of events, one concerning a very specific group of individuals ("County elections", social events, conferences etc) where online communities emerge due to offline events. The other is around real word events like "London bombings" or "Hurricane Katrina": both of which are examples of events that cut across community boundaries and which invoke reaction from almost every part of the blogosphere and almost in unison. In such cases on might see that the original community affiliation of the bloggers dont matter and tech, politics, religion and every other community might be talking about the same issue.
Exploiting Social Relations for Query Expansionand Result Ranking
Matthias Bender, Tom Crecelius, Mouna Kacimi, Sebastian Michel, Thomas
Neumann, Josiane Xavier Parreira, Ralf Schenkel, Gerhard Weikumza
This paper was presented by Mouna Kacimi.
This paper is about Query expansion in social networks and addresses the question of defining the valuable content to users in rich, online communities. Mouna suggests that one way to improve the search experience is by utilizing the social network information. The paper defines a social graph and provides scoring mechanism for finding and ranking relevant content for each node. In social networks, users can be both producers and consumers of information.Typically, the user has documents (photos, posts, etc) and tags. There are relations between nodes of the same type, for example
Further there can be relations between nodes of different types:
This paper presents a generic framework for ranking relevant information for a given user; by utilizing the various elements of the social information. The scoring model can be thought of as a means of querying what your friends think about the relevance of the given information. It combines the following pieces of information:
Note that the authors have considered an independence assumption in computing the scores. I am not certain if this is a good assumption, but it would be one simple way of combining the scores.
In order to do query expansion, i "ask" my friends about Paris, friend's documents about paris are retrieved and other similar tags are obtained. These are used to compute the query expansion. Friendship strength is computed using the "social distance" while the tag similarity is computed based on co-occurence of the tags.
I was surprised by their finding that social search works better in flickr but not very well in del.icio.us. I think that this is because the social networks of del.icio.us are very sparse. The meaning of friendship is also different here (aka friends and fans).
However, Mouna also pointed out that an improved version of their technique has been accepted at SIGIR 2008 and has a more detailed analysis. I look forward to checking out their extended paper. What I really liked about this paper was that it was a generic framework for combining social information (network, tags, documents, etc) and can be extended in ways that would be suitable for a particular type of network or task.
The Data Engineering for Blogs, Social Media and Web 2.0 workshop was held in conjunction with ICDE 2008. There were some really interesting papers and the invited talk was given by Prof. Ravi Sandhu. I had the opportunity to present some of our work at this workshop. My talk was about "Communities in Social media" which was about some of our recent work on "Approximating the Community Structure of the Long Tail" (ICWSM) and an overview of our previous and recent research in this area.
As Matt noticed already, not all the authors have their papers online, yet. I am still trying to figure out what the IEEE conference policy is for uploading the PDFs of the papers on the workshop website. Perhaps, I shall try to request the authors to upload the copies and link to them from the workshop website. In the following series of posts, I will share some of my notes from the different talks.
And oh yesss! the fact that the conference was in Cancun was just great! :-D
