SINCERE (Social Interactive Networking & Conversation Entropy Ranking Engine)

Rezaur made the SINCERE Social Search Engine available -- here is the Link: http://rahman.cs.ucdavis.edu/SINCERE/Search.html

Social network user lifetime

A new article -- http://rd.springer.com/article/10.1007/s13278-012-0066-8

Some of our recent research papers (and links)

(1) High-level -- this was an article published in Nature, Feb 2010, covering four projects under Future Internet Design (and ours is one of them):
 
http://www.nature.com/news/2010/100203/full/463602a.html

(2) Social Network Analysis and Model -- these papers reflect our works on applying social network analysis techniques to mainly online social media (e.g., Facebook, Twitter, LiveJournal, BuzzNet,..) and tried to interpret the data sets with existing or new models:

==> J. Lang, M. Spear, S.F. Wu
SOCIAL MANIPULATION OF ONLINE RECOMMENDER SYSTEMS
In SocInfo'2010: Proceedings of the 2nd International Conference on Social Informatics, Laxenburg, Austria
http://dsl.ucdavis.edu/lab_website/papers/lang_socinfo_10.pdf

==> M. Doroud, P. Bhattacharyya, S.F. Wu, and D. Felmlee
THE EVOLUTION OF EGO-CENTRIC TRIADS: A MICROSCOPIC APPROACH TOWARD PREDICTING MACROSCOPIC NETWORK PROPERTIES
to appear in IEEE SocialCom'2011, Boston, October 9-11, 2011
http://dsl.ucdavis.edu/~wu/DSL/SocialCom2011_Mina_Final.pdf

==> S. Ye, and S.F. Wu
Estimating the Size of Online Social Networks
to appear in the International Journal of Social Computing and Cyber-Physical Systems, 2011
http://dsl.ucdavis.edu/~wu/DSL/journal.pdf

==> S. Ye, and S.F. Wu
MEASURING MESSAGE PROPAGATION AND SOCIAL INFLUENCE ON TWITTER.COM
In SocInfo'2010: Proceedings of the 2nd International Conference on Social Informatics, Laxenburg, Austria
http://dsl.ucdavis.edu/~wu/DSL/003_TrustCCRI_Twitter_YeWu_2010.pdf

==> J. Lang, S.F. Wu
SOCIAL NETWORK USER LIFE TIME
ASONAM'2011: International conference on Advances in Social Network Analysis and Mining, Taiwan, 2011
http://dsl.ucdavis.edu/~wu/DSL/LifeTime_ASONAM2011.pdf

==> J. Lang, S.F. Wu
ANTI-PREFERENTIAL ATTACHMENT: IF I FOLLOW YOU, WILL YOU FOLLOW ME?
to appear in IEEE SocialCom'2011, Boston, October 9-11, 2011
http://dsl.ucdavis.edu/~wu/DSL/SocialCom2011_Juan_growth.pdf

(3). Papers about Trust (Trust is a really big issue, and the following papers merely represent a sample of space) --

==> Dimitri DeFigueiredo, Earl Barr, and S.F. Wu
Trust Is in the Eye of the Beholder
In PASSAT '09: Proceedings of 2009 IEEE International Conference on Privacy, Security, Risk and Trust, Vancouver, Canada, 2009.
http://dsl.ucdavis.edu/~wu/DSL/DSL_Beholder_PASSAT_2009.pdf

==> M. Spear, X. Lu, N. Matloff, and S.F. Wu
KarmaNET: Leveraging Trusted Social Paths to Create Judicious Forwarders
In IFCIN '09: Proceedings of the First International Conference on Future Information Networks, Beijing, China, 2009.
http://dsl.ucdavis.edu/~wu/DSL/DSL_KarmaNet_ICFIN_2009.pdf

==> M. Spear, X. Lu, N. Matloff, and S.F. Wu
A Formal Model to Analyze and Compare Reputation Systems for Distributed Networks (draft, not yet submitted)
http://dsl.ucdavis.edu/~wu/DSL/009_TrustCCRI_DistributedTrustFormalModel_SpearLuMatloffWu_2010.pdf

==> L. Banks, and S.F. Wu
Toward a Behavioral Approach to Privacy for Online Social Networks
In SocInfo'2010: Proceedings of the 2nd International Conference on Social Informatics, Laxenburg, Austria
http://dsl.ucdavis.edu/lab_website/papers/banks_socinfo_10.pdf

(4) papers about Wikipedia and Search Engine based on Social Informatics, these works are the "application-oriented" (i.e., how can Social Informatics be useful/leveraged to support existing critical applications).

==> H.Zhao, W. Kallander, T. Gbedema, H. Johnson, S.F. Wu
READ WHAT YOU TRUST: AN OPEN WIKI MODEL ENHANCED BY SOCIAL CONTEXT
to appear in IEEE SocialCom'2011, Boston, October 9-11, 2011
http://dsl.ucdavis.edu/~wu/DSL/SocialCom2011_KevinZhao_TrustWiki.pdf

==> P. Bhattacharyya, S. Ye, S.F.Wu, H. Johnson, K. Haigh
YOUR BEST MIGHT NOT BE GOOD ENOUGH: SEARCH DIVERSITY VIA SOCIAL NETWORK ANALYSIS (Invited Paper, the link to an earlier draft)
CollaborativeCom'2011: 7th International Conference on Collaborative
Computing: Networking, Applications and Worksharing
http://dsl.ucdavis.edu/~wu/DSL/SocialRank_SocialCom2011_submitted.pdf

==> H.Zhao, S. Ye, P. Bhattacharyya, K. Gribble, J. Rowe, S.F. Wu
SocialWiki: Bring Order to Wiki Systems with Social Context
In SocInfo'2010: Proceedings of the 2nd International Conference on Social Informatics, Laxenburg, Austria
http://dsl.ucdavis.edu/lab_website/papers/zhao_socinfo_10.pdf

==> P. Bhattacharyya, A. Garg and S.F. Wu,
Analysis of User Keyword in Online Social Networks
In Social Networks Analysis and Mining Journal (by Springer), 2010
http://dsl.cs.ucdavis.edu/~prantik/docs/snam10_keyword.pdf

(5) System/Architecture papers

==> R. Lee, R. Nia, S. Ye, J. Hsu, K. Levitt, J. Rowe and S.F. Wu
Design and Implementation of FAITH, An Experimental System to Intercept and Manipulate Online Social Informatics
ASONAM'2011: International conference on Advances in Social Network
Analysis and Mining, Taiwan, 2011
http://dsl.ucdavis.edu/~wu/DSL/FAITH_ASONAM2011.pdf

==> T. Tran, J. Rowe, S.F. Wu
Social Email: A Framework and Application for More Socially-Aware Communications
In SocInfo'2010: Proceedings of the 2nd International Conference on Social Informatics, Laxenburg, Austria
http://dsl.ucdavis.edu/lab_website/papers/tran_socinfo_10.pdf

Trustworthy Social Informatics: a Relationship-Centric Networking Paradigm

http://www.euroview2011.com/program/

My slides can be found under:
http://dsl.cs.ucdavis.edu/~wu/DSL/DSLFAITH_SFelixWu_EuroView_0801_2011.pptx

regarding "If This Then That" (ifttt)

I just read some ideas about IFTTT (see http://blog.ifttt.com/post/2316021241/ifttt-the-beginning).

While I certainly like to find out more technical details, it appears to me that this is another interoperability feature that DSL_FAITH should consider to offer, for example, between Google+ and Facebook under FAITH.

Your best might not be good enough -- re-thought on search engine

From our recent submission (Prantik is the first author):

The primary objective of a web-search engine like Google is to find and index the best content entry (or entries) for some given keywords, where best is usually based on some form of popularity through link analysis algorithms [1]–[3]. If the target of the search is either well-known/established (e.g., Newtons Laws of Motion) or clearly controversial (e.g., Californias Proposition 8 on Marriage Protection Act), then Google (or Wikipedia) can provide very nice information entries covering the target topics. However, if a topic is either dominated by a small school of thoughts or still on the converging process from various random ideas, the model of ranking based on popularity might not effectively help an individual in quickly identifying what he is really looking for. For a good example of ourselves, for the keywords of “Future Internet Design”, we had to flip five search results pages under Google before we can find the first link (http://goo.gl/KrO4B [4], results retrieved on June 20, 2011) about our Davis Social Links project [5].

Information is also about who have written, read, and shared about the information, and more importantly, how those social entities (e.g., readers/authors) are related to ‘us’ in interpreting and ranking that particular piece of information. For ‘Future Internet Design’, those who are related to our
research team socially should have a better chance to find out about our particular thought on this converging topic. We believe that the integration and correlation of sharable information content on the Internet and the on-line social informatics (i.e., relationships and interactions) is a possible direction to help our society in resolving the conflict between the quantity and the personalized quality during an information search process. The process of a user sharing URL(s) with friends leads to an integration of the web graph with the social network graph. The integration of the two networks helps in the growth of a trusted web where random pieces of articles from the web find support in the social network and user attempts at finding relevant articles for queries can boost from URL(s) that have been already read and shared by their friends for their relevancy.