A New Research Agenda: The Emergence of Online Social Networking Systems
Stefan Sariou and Nick Koudas
Department of Computer Science
University of Toronto
In this talk, Stefan discussed about research work that their groups are doing with studying and improving online social networking systems. Before, you didn't see much work in Computer Science on this area, but now, this is a hot topic with fertile areas for research. Specifically, Stefan is looking at social networks for access control to content, search, and content delivery and aggregation. Stefan is researching on social networking-based access for personal content. He says that the push model is an inefficient way to share content. For example, e-mail is a push model and e-mail was never designed to push content. Another way to share content is to use social networking sites for sharing content. However, sharing content online is a mess because you can start creating so many social identities and be part of so many social networks as a result. In real life, users have just one social network, but online, they have multiple social networks from different social networking sites. For example, you may have an account on Flickr, LinkedIn, YouTube, MySpace and Facebook, and you have social networks in these sites. But the people that are in your actual social network, is just one network. The online networks are just instances of your own social network. Therefore, there is a need to separate social information from content serving. I wholeheartedly agree with this.
Therefore, Stefan says that people should manage their social networks and maintain one social network. Everyone has a personal address book which they are familiar with and use. Let sites serve content and offer access control based on your social network in your address book. He says that there should not be a person or company that should manage your social network or even aggregate social networks, something of which Google is trying to do to create one huge social network (aggregations of multiple social networks combined together).
So from this, Stefan's research group is looking and developing new internet applications: Social Flickr will be released November 2007, Social BitTorrent in December 2007, and Social Google calendar in January 2008. Those are pretty aggressive time schedules for releasing the software.
Nick's work deals with social media aggregation to build a system to share information with others. His research group has created a system called BlogScope that mines the blogs in the blogosphere and it is currently tracking over 14.28 million blogs with 127.61 million posts. BlogScope can assist the user in discovering interesting information from these millions of blogs via a set of numerous unique features including popularity curves, identification of information bursts, related terms, and geographical search. From social media, based on content, we can extract communities for recommendation (which I believe they could use my work).
On Technorati: social networking symposium, blogscope
Friday, November 02, 2007
Conversations in Social Hypertext: Telecommunity and Post-Industrial Work - Social Networking Conference @ U of T
Conversations in Social Hypertext: Telecommunity and Post-Industrial Work - Social Networking Conference @ U of T
Mark Chignell
Department of Mechanical and Industrial Engineering
University of Toronto
In this talk, Mark talked about social computing tools for telework using a software that the Interactive Media Lab created called Vocal Village which is a great tool for spatializing audio (better than Skype!). The software was tested in a Japanese company. As well, Mark introduced work about looking at community in online environments, specifically the vaccination groups which is part of my PhD research work.
On Technorati: social networking conference, Vocal Village, Interactive Media Lab
Mark Chignell
Department of Mechanical and Industrial Engineering
University of Toronto
In this talk, Mark talked about social computing tools for telework using a software that the Interactive Media Lab created called Vocal Village which is a great tool for spatializing audio (better than Skype!). The software was tested in a Japanese company. As well, Mark introduced work about looking at community in online environments, specifically the vaccination groups which is part of my PhD research work.
On Technorati: social networking conference, Vocal Village, Interactive Media Lab
Content-based Social Network Analysis of Online Communities - Social Networking Conference @ U of T
Content-based Social Network Analysis of Online Communities
Anatoliy Gruzd and Caroline Haythornthwaite
School of Library and Information Science, University of Illinois
In this talk, they analyze online communities like bulletin boards to gain more information and insight about nodes, relations and ties. Very few systems look at relational information so they focus on nodes and tie discovery. Their goal is to identify who are the actors in the network. Their approach is to use natural language processing to enhance the current techniques of building social networks. So how to obtain the social networks from online communities? There are two methods. First, you can do a chain network which is based on the chain of posting of posts and comments (like what I do for my PhD research). One of the problems with the chain network (which I also encountered as well) is what is the relation of the 3rd commenter, do they comment on the posting or the previous comment? A solution around this is to look at tie strength to the previous commenter or the poster to determine if the person is posting to the previous commenter or the poster. The second method is to do a name network by pulling the names from within the body of the text. Here is where the NLP comes into play.
The idea in the name network is to make use of node and information in text of posting. How to disambiguate names/nicknames from text, those that mean the same person. How to know the name is in the subject, is it being discussed? To determine this, they did hand coding of the items to see the categories of names. They then compared the name network with the chain network and performed ego network analysis for posts and comments. Another problem is that many times when you reply, the previous message is embedded in the post so you don't want to include this in the name generator to duplicate this. So, they removed the previous message embedded in the reply to the post.
Anatoliy Gruzd and Caroline Haythornthwaite
School of Library and Information Science, University of Illinois
In this talk, they analyze online communities like bulletin boards to gain more information and insight about nodes, relations and ties. Very few systems look at relational information so they focus on nodes and tie discovery. Their goal is to identify who are the actors in the network. Their approach is to use natural language processing to enhance the current techniques of building social networks. So how to obtain the social networks from online communities? There are two methods. First, you can do a chain network which is based on the chain of posting of posts and comments (like what I do for my PhD research). One of the problems with the chain network (which I also encountered as well) is what is the relation of the 3rd commenter, do they comment on the posting or the previous comment? A solution around this is to look at tie strength to the previous commenter or the poster to determine if the person is posting to the previous commenter or the poster. The second method is to do a name network by pulling the names from within the body of the text. Here is where the NLP comes into play.
The idea in the name network is to make use of node and information in text of posting. How to disambiguate names/nicknames from text, those that mean the same person. How to know the name is in the subject, is it being discussed? To determine this, they did hand coding of the items to see the categories of names. They then compared the name network with the chain network and performed ego network analysis for posts and comments. Another problem is that many times when you reply, the previous message is embedded in the post so you don't want to include this in the name generator to duplicate this. So, they removed the previous message embedded in the reply to the post.
Social Networking conference at U of T
I just finished presenting my talk on "Structural Analysis of Social Hypertext for Finding Sense of Community" at the Social Networking conference at U of T this morning. The gremlins of presentation attacked me today. During the last couple of slides of my talk, I accidentally kicked the AC plug (which seemed to happen to the previous speaker), and then the digital projector turned off. So, I had to finish my talk without slides, but I was fortunate that I could still read the slides off the laptop and my notes, though I wasn't quite happy with that and it kind of throwed me off. Second of all my slides didn't show up properly on the laptop in the room, normally I use the laptop in the room instead of mine to avoid switching and having my laptop reboot in the process (it's actually happened couple of times, the last time at the CASCON conference). Third, I recorded the talk on my iPod but for some strange reason it actually didn't save on the iPod (it actually didn't even start recording). Aghh!
But I do have the slides from my talk so the slides that I wanted to show, are available on my web site.
This is the first time where I could not rely on the laptop in the room, than use my own laptop.
Anyways, if you have any comments on my talk, feel free to contact me at my e-mail (achin AT cs DOT toronto DOT edu).
But I do have the slides from my talk so the slides that I wanted to show, are available on my web site.
This is the first time where I could not rely on the laptop in the room, than use my own laptop.
Anyways, if you have any comments on my talk, feel free to contact me at my e-mail (achin AT cs DOT toronto DOT edu).
Tuesday, October 30, 2007
Jon Kleinberg CS lecture at U of T
Right now is the lecture by Jon Kleinberg, Department of Computer Science, Cornell University which is on Challenges in Mining Social Network Data: Processes, Privacy and Paradoxes. He has generated seminal results in social networks and document retrieval. I've read his research work on the HITS algorithm which uses hubs and authorities in order to classify search, and from which Google's PageRank is somewhat related to. I've never heard Jon speak so I'm very glad to hear him speak.
He will also speak tonight to kick off the Social Networking Week at U of T. What can computer science contribute to social networks? Today there is a convergence of social and technological networks, computing and information systems with intrinsic social structure. Social network data is a very active area in sociology, social psychology and anthropology. So what can the different fields learn from each other (sociology, social psychology, anthropology from computer science)? This is the research area which I am also part of as well, and it's an exciting research area in my opinion with the emergence of social networking sites like Facebook and MySpace. Mining social networks has a long history in social sciences eg. with Wayne Zachary's PhD work on the university karate club, observing social ties and rivalries. Split in the network could be explained by the minimum cut in the social network.
Social network data spans many orders of magnitude. For example there were 240 million nodes of all IM communication over one month on Microsoft Instant Messenger (Leskovec-Horvitz '07), 4.4 million nodes of declared friendships on blogging community LiveJournal (Liben-Nowell et al., 2005). How can we find the point where the lines of research in large scale and small scale networks converge? In social networks, we can find behaviours of diffusion in social networks that cascade from node to node like an epidemic, which is identified by radial structures in the graph. There have been empirical studies of diffusion in the social sciences like the spread of new agricultural and medical practices (Coleman et al., 1966). The diffusion curves are based on the probability of adopting new behaviour which depends on number of friends who have adopted (Bass 1969, Granovetter 1978 and Schelling 1978). All of the diffusion curves seem to have diminishing returns property, for example in editing a Wikipedia article (Cosley et al., 2007) and joining a LiveJournal community (Backstrom et al., 2006).
These results can then be used for general prediction. Given a network and v's position in it at t1, estimate the probability v will join a given group by t2. Kleinberg has formulated this as a probability estimation problem (Backstrom-Huttenlocher-Kleinberg-Lan 2006). Do disconnected friends or connected friends make joining more likely? Disconnected friends provide an informational advantage but connected friends provide safety/trust advantages. For example in LiveJournal, joining probability increases significantly with more connections among friends in the group (in otherwise friends that are within a clique than not).
If connectedness among friends promotes joining, do highly "clustered" groups grow more quickly? Kleinberg defines clustering to be # of triangles / # of open triads and you can determine community by examining the growth from t1 to t2 as a function of clustering. Leskovec, McGlohon, Faloutsos, Glance and Hurst (2007) have looked into the diffusion of topics in networks of news media and bloggers which shows cascading behaviour. Leskovec, Adamic and Huberman (2006) describe how incentives can be used to propagate interesting recommendations along social network links. How to push questions to people within the social network? (Kleinberg, Raghavan, 2005)
One of the most important questions in mining social network data is how to protect privacy in the dataset. There has been some research where anonymizing data actually caused problems from using on-line pseudonyms and using search engine query logs. If you are part of a small network and based on connectivity, you may be able to find yourself, so anonymization doesn't help. An attacker can attack an anonymized network by being part of the system. Kleinberg has done some work on this by creating a template (Backstrom, Dwork, Kleinberg, 2007). The idea is an attacker creates a small network of nodes through creating accounts called subgraph H and attach them to targeted nodes in the original network. From Ramsey theory, in a random n-node graph, H is unique.
Take home message: how do we build deeper models of the processes at work inside large-scale social networks? How do we make data available without compromising privacy?
It was great to finally meet and talk with Jon Kleinberg!
On Technorati: jon kleinberg, social network
He will also speak tonight to kick off the Social Networking Week at U of T. What can computer science contribute to social networks? Today there is a convergence of social and technological networks, computing and information systems with intrinsic social structure. Social network data is a very active area in sociology, social psychology and anthropology. So what can the different fields learn from each other (sociology, social psychology, anthropology from computer science)? This is the research area which I am also part of as well, and it's an exciting research area in my opinion with the emergence of social networking sites like Facebook and MySpace. Mining social networks has a long history in social sciences eg. with Wayne Zachary's PhD work on the university karate club, observing social ties and rivalries. Split in the network could be explained by the minimum cut in the social network.
Social network data spans many orders of magnitude. For example there were 240 million nodes of all IM communication over one month on Microsoft Instant Messenger (Leskovec-Horvitz '07), 4.4 million nodes of declared friendships on blogging community LiveJournal (Liben-Nowell et al., 2005). How can we find the point where the lines of research in large scale and small scale networks converge? In social networks, we can find behaviours of diffusion in social networks that cascade from node to node like an epidemic, which is identified by radial structures in the graph. There have been empirical studies of diffusion in the social sciences like the spread of new agricultural and medical practices (Coleman et al., 1966). The diffusion curves are based on the probability of adopting new behaviour which depends on number of friends who have adopted (Bass 1969, Granovetter 1978 and Schelling 1978). All of the diffusion curves seem to have diminishing returns property, for example in editing a Wikipedia article (Cosley et al., 2007) and joining a LiveJournal community (Backstrom et al., 2006).
These results can then be used for general prediction. Given a network and v's position in it at t1, estimate the probability v will join a given group by t2. Kleinberg has formulated this as a probability estimation problem (Backstrom-Huttenlocher-Kleinberg-Lan 2006). Do disconnected friends or connected friends make joining more likely? Disconnected friends provide an informational advantage but connected friends provide safety/trust advantages. For example in LiveJournal, joining probability increases significantly with more connections among friends in the group (in otherwise friends that are within a clique than not).
If connectedness among friends promotes joining, do highly "clustered" groups grow more quickly? Kleinberg defines clustering to be # of triangles / # of open triads and you can determine community by examining the growth from t1 to t2 as a function of clustering. Leskovec, McGlohon, Faloutsos, Glance and Hurst (2007) have looked into the diffusion of topics in networks of news media and bloggers which shows cascading behaviour. Leskovec, Adamic and Huberman (2006) describe how incentives can be used to propagate interesting recommendations along social network links. How to push questions to people within the social network? (Kleinberg, Raghavan, 2005)
One of the most important questions in mining social network data is how to protect privacy in the dataset. There has been some research where anonymizing data actually caused problems from using on-line pseudonyms and using search engine query logs. If you are part of a small network and based on connectivity, you may be able to find yourself, so anonymization doesn't help. An attacker can attack an anonymized network by being part of the system. Kleinberg has done some work on this by creating a template (Backstrom, Dwork, Kleinberg, 2007). The idea is an attacker creates a small network of nodes through creating accounts called subgraph H and attach them to targeted nodes in the original network. From Ramsey theory, in a random n-node graph, H is unique.
Take home message: how do we build deeper models of the processes at work inside large-scale social networks? How do we make data available without compromising privacy?
It was great to finally meet and talk with Jon Kleinberg!
On Technorati: jon kleinberg, social network
Monday, October 29, 2007
Busy busy week this week
I've got a busy week ahead of me for this week. I'm giving an Ignite presentation about finding subgroups in TorCamp at DemoCampToronto15 tonight at Hart House, then have to finish marking assignments, then finish writing a paper, and then giving a talk at the Social Networking Week at U of T on Friday.
But I enjoy doing this kind of stuff, so I don't mind it. So don't expect too many blog entries this week!
But I enjoy doing this kind of stuff, so I don't mind it. So don't expect too many blog entries this week!
Wednesday, October 24, 2007
Pervasive 2007 Conference trip report in IEEE Pervasive Computing magazine
Just found out that the Pervasive 2007 conference trip report which I helped co-author is now out in the IEEE Pervasive Computing magazine Vol. 6 No. 4 (October - December 2007). You can read the article here.
On Technorati: Pervasive2007
On Technorati: Pervasive2007
Finished my CASCON short paper talk
I just finished my CASCON short paper talk on "Identifying Active Subgroups in Online Communities" about an hour ago. It went well, I had some great feedback. I'll post the talk which I recorded and slides soon. Now, I can concentrate on the rest of my PhD work. No rest for a PhD student! But I enjoy giving talks and meeting with people and discussing about my research, it's exciting and engaging. If you have any comments or feedback from my paper or talk, write some comments on this blog back to me!
Tuesday, October 23, 2007
CASCON 2007 Conference, Day 1
I just finished co-chairing a session on Tagging as a Social Contract along with Mark Chignell and Sara Darvish, where we had 4 talks about issues surrounding tagging in a business environment. This was the second session as part of the Second Working Conference on Social Computing and Business at the CASCON 2007 conference. It was a great workshop and great session, and great discussion. I talked about how community can be inferred from tagging using the YouTube vaccination videos as an example. Podcasts and slides from the workshop should be available, so check the CASCON blog.
I also showed a demo of a community-based web portal that our lab created to support vaccination groups in our exhibit at the Technology Showcase called "Video Web 2.0: Collaborative Tagging in Web Video". If you're at CASCON, check it out!
Photos from CASCON are on my Flickr account.
Friday, October 19, 2007
Google hints at social network plan
I've been wondering when Google would start to think about social networking and how it could be used. So far, Yahoo has been the leader in social networking, with Flickr and Upcoming and Yahoo My Web Beta. Google's Orkut still does not compare in the same calibre with Facebook or MySpace, huge social networking web sites. However, Google is now beginning to hint how they will use social networking data in their own web search and to share the social data with others. According to Eric Schmidt, Google's CEO, from this article from NY Times, Google has something up its sleeve.
Will Google be able to top Yahoo and other social networking sites like Facebook? Only time will tell.
Will Google be able to top Yahoo and other social networking sites like Facebook? Only time will tell.
Wednesday, October 17, 2007
Passed the thesis proposal!
I just did my thesis proposal today and passed! Just need to make changes and do some more analysis and I should be hopefully done before April of next year.
Saturday, October 13, 2007
Thesis proposal and busy rest of October!
I just finished writing the thesis proposal which I will send to my committee, because I will have a meeting with them on Wednesday. Hopefully, everything goes well and if everything goes according to plan, I can finish the dissertation and defence by end of this year!
It's going to be a busy rest of the October. I'm co-chairing a workshop at CASCON called Tagging as a Social Contract on Monday, October 22. If you're going to be at CASCON, sign up for this workshop, it promises to be an interesting one. For more information, check the CASCON blog. After that, I'm going to be presenting my paper at the CASCON conference on Wednesday, October 24 called "Identifying Active Subgroups in Online Communities". And then, I will be giving a talk at the Social Networking Symposium at U of T on Friday, November 2nd from 9:50 to 10:15 am called "Structural Analysis of Social Hypertext for Finding Sense of Community" right after my supervisor talks.
It's going to be a busy rest of the October. I'm co-chairing a workshop at CASCON called Tagging as a Social Contract on Monday, October 22. If you're going to be at CASCON, sign up for this workshop, it promises to be an interesting one. For more information, check the CASCON blog. After that, I'm going to be presenting my paper at the CASCON conference on Wednesday, October 24 called "Identifying Active Subgroups in Online Communities". And then, I will be giving a talk at the Social Networking Symposium at U of T on Friday, November 2nd from 9:50 to 10:15 am called "Structural Analysis of Social Hypertext for Finding Sense of Community" right after my supervisor talks.
Monday, October 08, 2007
Married!
Yes, I just got married about a week ago, the wedding was great and the weather was just perfect. Couldn't have asked for a better day. Thanks to everyone who helped out in the wedding and for those that attended. My wife and I were so happy to see you there, and even though it was a tiring day, we thoroughly enjoyed it and will treasure this for the rest of our lives.
I'm very thankful this Thanksgiving for such a beautiful, amazing and considerate wife. And marriage life feels so great, I wouldn't trade it for anything else.
For those that are interested, I'll post wedding photos online soon.
I'm very thankful this Thanksgiving for such a beautiful, amazing and considerate wife. And marriage life feels so great, I wouldn't trade it for anything else.
For those that are interested, I'll post wedding photos online soon.
Thursday, September 13, 2007
Thanks for a great Hypertext conference!
I'd like to thank all the organizers for a great Hypertext conference! I thoroughly enjoyed it and meeting with lots of familiar faces and new ones. To remember the moments we shared together, I have placed all the photos that I took from the conference on my Flickr site. I had some people come to me to ask if I would put some notes from the talks on my blog. I'll do that when I have time and head back to Toronto.
See you all in Pittsburgh in Hypertext 2008!
On Technorati: Hypertext07, Hypertext2007
See you all in Pittsburgh in Hypertext 2008!
On Technorati: Hypertext07, Hypertext2007
Tuesday, September 11, 2007
Day 2 of Hypertext conference
I'm at the Hypertext conference on Day 2. Some interesting talks on semantic web, web accessibility and user profiles. I'm really enjoying this conference, meeting lots of interesting work and interdisciplinary research. I'm going to present my research work tomorrow at 12 pm on Identifying Subcommunities Using Cohesive Subgroups in Social Hypertext. If you're at the conference, come and attend my talk!
More photos from yesterday and today are on Flickr.
On Technorati: Hypertext07
More photos from yesterday and today are on Flickr.
On Technorati: Hypertext07
Monday, September 10, 2007
End of Day 1 session at Hypertext conference
Just finished the end of the technical sessions at the Hypertext conference, and am now in the Graduate BOF where there are lots of grad students chit chatting and just socializing. Then, there will be the SIGWEB business meeting and then the tour of the Manchester Museum.
Day 1 of Hypertext 2007 conference
Today is Day 1 of the Hypertext 2007 conference and I'm in Manchester, UK. Yesterday, I did my own tour around Manchester, going to the Whitworth Art Gallery and going to Curry Mile which is the Indian and Pakistanian area of Manchester of restaurants. Pictures of that and today's first day are available on Flickr.
Thursday, September 06, 2007
Hypertext conference starts next week
There's only 4 days until the Hypertext conference starts in Manchester, England. It looks to be a great programme of papers and events. I'll be presenting my paper on "Identifying Subcommunities in Social Hypertext" on September 12 at 12 pm, yes right before lunch!
I look forward to meeting with people from last year's Hypertext which I presented, and meeting with new people.
On Technorati: hypertext07
Tuesday, September 04, 2007
Difference between social graph, social network web site, and social OS
Here's an article that explains what's the difference between a social graph, social network web site and social OS. An example of a social graph is the people connected to each other. AN example of a social network web site is Flickr or Twitter. An example of a social OS is Facebook, although I don't really kind of agree with that. I think of Facebook as a social network application or social network web site. It's not really an OS, because it doesn't permeate through all my computer's applications and it's not tied with Windows or Linux. All my applications I'm using do not all tie in with Facebook (at least not yet).
What do you all think about this?
What do you all think about this?
Monday, September 03, 2007
Gmail redirects to garbled site
Yesterday, something strange happened. For some reason, when I went to Gmail, it would redirect me through ora.3168a.com to a garbled web page. I thought that I had contracted a virus or spyware, so I used Norton Antivirus and Lavasoft Ad-Aware to check, but found nothing. I tried to check Gmail with Internet Explorer, and it would also cause the same problem. I then cleared out the cache and history, and tried to access Gmail but I still got the garbled web page. This really puzzled me, so I tried to isolate the problem if it was a machine problem, by going to another computer and accessing Gmail from there. On another laptop, it was fine. Oh by the way, I was using Mozilla Firefox browser. But then when I went to another computer in the house, with Gmail, I still got the same redirect. What was worse was that not even Gmail but other web sites were redirecting through ora.3168a.com. Doing a Google search on ora.3168a.com resulted in a list of malicious and spam web sites of which ora.3168a.com was on the list.
I found out that another person also had the same problem as well, but apparently he was able to solve it by going through some several reboots and following some removal instructions translated from Japanese. I didn't do that, but today it seems like I can read Gmail now. It's kinda scary though what happened.
I found out that another person also had the same problem as well, but apparently he was able to solve it by going through some several reboots and following some removal instructions translated from Japanese. I didn't do that, but today it seems like I can read Gmail now. It's kinda scary though what happened.
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