Social Mobile Web 2009

I am looking forward to reviewing interesting papers for the Social Mobile Web 2009 workshop. We have very cool Program Committee members and I am happy to be part of the group. Mobile devices are everywhere and I would love to see innovations coming out in this area.

Call for Paper:

The mobile space is evolving at an astonishing rate. At present there are over 3.5 billion mobile subscribers worldwide and with continued advances in devices, services and billing models, the mobile web looks set to inspire a new age of anytime, anywhere information access. The inherent characteristics of mobile phones enable new types of interactions, e.g. mobile phones are personal to the individual, they are always on and always connected. And as such we are seeing a shift towards mobile devices for social mediated tasks. The world is also witnessing an explosion in social web services. Online social networking sites such as Facebook and MySpace continue to experience huge increases in usage, with more and more users seeking novel ways of interacting with their friends and family.

Topics:
Novel social interactions on mobile devices.
Social mobile content sharing and distribution services.
Context aware mobile services - beyond location based services.
Social mobile search and social mobile browsing.
User evaluations of social mobile services.
Mobile user interfaces that incorporate social elements.
Mobility and social networks.
Models of mobile social behavior and mobile traces.
Urban gaming, mobile mixed reality, etc.
Innovative social mobile applications.

Deadline: May 11th 2009

Plotting Venn diagrams

I'm having fun with this marvelous program Twitter Venn: a program that takes in search keywords and plots a Venn diagram that represents the overlap in the use of keywords in Twitter messages.  Making of this application appear in Jeff Clark's blog.

Twitter makes the search possible online (search.twitter.com), which allowed this to happen. Very nice. I want to make more sophisticated Venn diagram: similar to the Google's key word trend, I'd like to see how the relationship evolves. Or a given keyword, I'd like to see the hottest matching set of keywords. 

BTW, what went happened with such small overlap in cat and sleep? Am I the only one with a cat that sleeps all day long?  

Crawling YouTube

I started crawling YouTube site (again!) to get video comments.  This time, I'm using Google Data API and properly approaching the site.  The API makes the code very short and I like that it runs fast. Here is a sample code for getting comments.

comment_feed=yt_service.GetYouTubeVideoCommentFeed(video_id=video_id)
for comment_entry in comment_feed.entry:
print comment_entry.ToString()

Strangely, the code gives me a subset of video comments (say 100), even when there are thousands of comments I can see in YouTube. I'll have to go through the documentation or switch back to wget and urlopen. 

PS: Crawling YouTube is rather distracting.  I ended up watching 20 cat videos and participated in viral spreading of those videos (i.e., sending spam video links to friends).  My favorite of the day: cat massage.

Summary of the ACM SNS workshop

Here is my summary of the recent ACM Social Network Systems 2009

* Security at a Large Social Network, Tao Stein (Facebook) 

Tao's talk started with the "The Road to 200 Million" article from NYT.  Facebook has three data centers, each in charge of a major continent: VA (asia) SC (europe), SF (us). Data consistency is hard to achieve, so Facebook only uses a single server for writing and the other servers for read only operations. Servers use 25TB of RAM for MySQL.

There are obviously lots of attacks on Facebook. Their long term goal is to achieve that one identity in the system corrsponds to one real identity.  In every security policy, trade-off is at site integrity and user experience: throwing in more CAPCHA will increase security, but then users experience will degrade.   

The #1 problem is at account takeovers. Here are a few example attacks:

(a) photo/video scam (e.g., "This applet will show you which friends viewed your photo")
(b) 419 attack by Nigirian spammers (e.g., "I am lost in London, please send me $1000 to Western Union") 
(c) koobface (a botnet that sends spam URLs)
(d) fake chain letter (e.g., "Facebook is overpopulated")

Often users use the same login credentials across multiple sites. (Yes, I do too!) So if one site gets compromised, then all are compromised. Because most sites force users to use complex password, uses end up using a common password across sites. Facebook tries a lot to educate users with sophisticated privacy setting.   

  

How is the network security different in online social network? (a) education and (b) coefficient (= strength of ties) in the social graph. 

*Botnets vs. Social Networks, Elie Bursztein (Stanford)
Second talk was by Elie, who is a post-doc at Stanford. Elie gave a brief overview on his research: how to turn online social networks into a botnet.   Elie found that a number of existing systems (e.g., MSN messenger) have vulnerabilities: a malicious user can send codes to turn his friends' (and their friends') host machines into a botnet. 


* Eight Friends Are Enough: Social Graph Approximation via Public Listings, Joseph Bonneau (University of Cambridge)
I greatly enjoyed this talk. The talk demonstrated how revealing limited information about a social network (e.g., Facebook's public listing, which shows 8 random friends of a user) can say so much about the entire social graph structure. 

I've heard a new term "social graph privacy". It means to prevent data aggregators from reconstructing large portions of the social graph, composed of users and their friendship links. Joseph said protecting social graph is more difficult than protecting personal data, because personal data can be managed individually by users, while information about a user's place in the social graph can be revealed by any of the user's friends. This work got popular in media.  I also saw BBC interview with the authors.

Geographic distance of social ties

Barry Wellman published an interesting article on geographic distance of social ties. Below is from his publication webpage.  I'm all intrigued.  I'll be soon posting stories on the Flickr counterpart.

"Does Distance Still Matter in the Age of the Internet?" (Diana Mok, Juan-Antonio Carrasco and Barry Wellman, Urban Studies, 2009).  Our study is part of the broad debate about the role of distance and technology for interpersonal contact. To the best of our knowledge, this is the first study that systematically and explicitly compares the role of distance in social networks pre- and post-Internet. We analyze the effect of distance on the frequency of email, phone, face-to-face and overall contact in personal networks, and we compare the findings with its pre-Internet counterpart whose data were collected in 1978 in the same East York, Toronto locality. We use multilevel models with spline specification to examine the nonlinear effects of distance on the frequency of contact. We compare these effects for both very close and somewhat close ties, and for different role relationships: immediate kin, extended kin, friends and neighbours. The results show that email contact is generally insensitive to distance, but tends to increase for transoceanic relationships greater than 3,000 miles apart. Face-to-face contact remains strongly related to short distances (within five miles), while distance has little impact on how often people phone each other at the regional level (within 100 miles). The study concludes that email has only somewhat altered the way people maintain their relationships. The frequency of face-to-face contact among socially-close friends and relatives has hardly changed between the 1970s and the 2000s, although the frequency of phone contact has slightly increased. Moreover, the sensitivity of these relationships to distance has remained similar, despite the communication affordances of the Internet and low-cost telephony.

ACM Social Network Systems 2009 Workshop

Tao Stein (@Facebook) and I are organizing a wonderful workshop in Nuremberg next Tuesday. We will have 8 paper presentations and 2 invited talks on security -- all look very interesting.

ACM Social Network Systems 2009

Program

0900 - 1000: Security at a Large Social Network, Tao Stein (Facebook)
1000 - 1030: Botnets vs. Social Networks, Elie Bursztein (Stanford)
1030 - 1100: Break

1100 - 1230: Privacy and Security
Eight Friends Are Enough: Social Graph Approximation via Public Listings
Joseph Bonneau, Jonathan Anderson, Ross Anderson, Frank Stajano (University of Cambridge)

Anonymous Opinion Exchange over Untrusted Social Networks
Mouna Kacimi (Max Planck Institute for Informatics), Stefano Ortolani (Vrije Universiteit), Bruno Crispo (University of Trento)
PeerSoN: P2P Social Networking - Early Experiences and Insights
Sonja Buchegger, Doris Schiöberg (TU Berlin, Deutsche Telekom Laboratories), Le Hung Vu (EPFL), Anwitaman Datta (NTU Singapore)

1230 - 1330: Lunch

1330 - 1500: The Ties that Bind
On the Strength of Weak Ties in Mobile Social Networks
Stratis Ioannidis, Augustin Chaintreau (Thomson)
Centralities: Capturing the Fuzzy Notion of Importance in Social Graphs
Erwan Le Merrer (INRIA), Gilles Tredan (University of Rennes 1)
Buzztraq: Predicting Geographical Access Patterns of Social Cascades using Social Networks
Nishanth Sastry, Eiko Yoneki, Jon Crowcroft (University of Cambridge)
1500 - 1530: Break

1530 - 1630: Personalizing Search
Towards Personalized Peer-to-Peer Top-K Processing
Xiao Bai, Marin Bertier (INSA de Rennes), Rachid Guerraoui (EPFL, Switzerland), Anne-Marie Kermarrec (INRIA Rennes, France)
Toward Personalized Query Expansion
Marin Bertier (INSA de Rennes, France), Rachid Guerraoui (EPFL, Switzerland), Anne-Marie Kermarrec, Vincent Leroy (INSA de Rennes, France)

Flash Floods and Ripples

My recent paper investigates the role of blogosphere as a social media. 

Flash Floods and Ripples: The Spread of Media Content through the Blogosphere. 

Meeyoung Cha, Juan Antonio Navarro Perez, and Hamed Haddadi
In Proc. of the AAAI Conference on Weblogs and Social Media (ICWSM) Data Challenge Workshop, San Jose, May 2009

We tracked down the occurrences of YouTube videos in blog posts and named the two key patterns we found: flash floods and ripples. Flash floods represent rapid cascade events, which we see in the spread of political videos. Ripples represent a slow propagation, which we see for old music videos. So just how rapid are flash floods? The graph below shows the time it took to propagate YouTube videos, based on their topics. News videos propagate by the hour and stop spreading after a week. Music videos continue to spread after several months.

Plot below shows the propagation pattern of one of the popular YouTube videos in the blogosphere. The video was an advertisement made by the Republican party for the U.S. Presidential Election, 2008. Like other news videos, it spread quickly in the network and was blogged about 79 times within a week!