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Monthly Archives: August 2013

A group of researchers at the University of Calgary have conducted an interesting research on countdown timers at intersections to see if they ever improve road safety and reduce collisions and car crashes. The result was very surprising. The device causes more crashes. The link is attached to this post. The explanation is convincing. But we can explain this surprising result from completely different aspect by social structures and drivers’ social behavior.

When we drive our cars in roads and highways, we, unintentionally, form a social structure by other drivers who drive in vicinity. Our social interaction with them is not to get very close in order to prevent any crash. Our collective behavior is to drive distant enough to have a safe drive. All these happen under a social and collective judgment which works properly most of the time. Adding technology such as countdown timer can distract the collective judgment because every driver has own interpretation from the number displayed on the timer.

The lesson we learn is that we have to be very cautious when we implement social recommendation tasks such as link and friend recommendation. The risk might be damaging organic social fabric. This is the criticism that we may have to “people you may know“ feature in LinkedIn and similar features in Facebook and Twitter. It seems the only objective is growing the network as fast as possible even with the cost of health of network.

Good examples of organic social fabric as channels to relay social and collective behavior are bird flocks and fish schools. There is no reported collisions or crash in bird flocks or fish schools although sometime tens of thousands of these species move in sync and harmony together. This might be because there are no nagging kid on the back seat, or catchy billboard ads, or sidewalk distractions, but the main reason is nothing distracts the collective behavior of birds and fish and this allows them behave based on their instinct.

Hi,

I am starting this blog as a unified environment for my personal web site (including my academic web site) and daily blog posts. I believe wordpress is a good platform for this purpose.

On th top pf this site (menue) you can find my permanent (timeless) pages including my contact info.

 

1. Node Classification in Social Networks

by: Smriti Bhagat, Graham Cormode, S. Muthukrishnan

2. Lexicon-based methods for sentiment analysis

by: Maite Taboada, Julian Brooke, Milan Tofiloski, Kimberly Voll, Manfred Stede

3. Sentiment in Twitter events

by: Mike Thelwall, Kevan Buckley, Georgios Paltoglou

4. Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena

by: Johan Bollen, Alberto Pepe, Huina Mao

5. Learning to Classify Threaten E-mail

by: Subramanian A. Balamurugan, Ramasamy Rajaram

 6. Twitter mood predicts the stock market

by Johan Bollen, Huina Mao, Xiao-Jun Zeng

7. Predicting Positive and Negative Links in Online Social Networks

by: Jure Leskovec, Daniel Huttenlocher, Jon Kleinberg

 8. You Are Who You Talk To: Detecting Roles in Usenet Newsgroups

by: D. Fisher, M. Smith, H. T. Welser

 9. Supervised Machine Learning Applied to Link Prediction in Bipartite Social Networks

by: Nesserine Benchettara, Rushed Kanawati, Celine Rouveirol

 10. Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction

by: Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda

 11. Suggesting friends using the implicit social graph

by: Maayan Roth, Assaf B. David, David Deutscher, Guy Flysher, Ilan Horn, Ari Leichtberg, Naty Leiser, Yossi Matias, Ron Merom

 12. Cold start link prediction

by: Vincent Leroy, Barla B. Cambazoglu, Francesco Bonchi

 13. Normalized Information Distance

by: Paul M. B. Vitanyi, Frank J. Balbach, Rudi L. Cilibrasi, Ming Li

14. Clustering by Compression

by: R. Cilibrasi, P. M. B. Vitanyi

15. An Iterative Hybrid Filter-Wrapper Approach to Feature Selection for Document Clustering

by: Mohammad-Amin Jashki, Majid Makki, Ebrahim Bagheri, Ali Ghorbani

 16. Estimating the number of clusters in a dataset via the Gap statistic

by: Robert Tibshirani, Guenther Walther, Trevor Hastie

17. Measures for Short Segments of Text

by: Donald Metzler, Susan Dumais, Christopher Meek

 18. Gender, Genre, and Writing Style in Formal Written Texts

by: Shlomo Argamon, Moshe Koppel, Jonathan Fine, Anat R. Shimoni

 19. A Social Network Analysis Approach to Detecting Suspicious Online Financial Activities

by: Lei Tang, Geoffrey Barbier, Huan Liu, Jianping Zhang

20. Using Social Network Analysis for Spam Detection

by: Dave DeBarr, Harry Wechsler

21. Information Distance

by: Bennett, Gacs, Li, Vitanyi, Zurek

22. Information Distance and Its Applications

by: Ming Li

 23. Combining Labeled and Unlabeled Data with Co-Training

by: Avrim Blum, Tom Mitchell

24. Learning from Imbalanced Data Sets: A Comparison of Various Strategies

by: Nathalie Japkowicz

25. One-class svms for document classification

by: Larry M. Manevitz, Malik Yousef