Category Archives: News

Social bot research featured on CACM, IEEE Computer covers

CACM-coverResearch on detection of social bots by CNetS faculty members Alessandro Flammini and Filippo Menczer, former IUNI research scientist Emilio Ferrara, and graduate students Clayton Davis, Onur Varol, and Prashant Shiralkar was featured on the covers of the two top computing venues: the June issue of Computer (flagship magazine of the IEEE Computer Society) and the July issue of Communications of the ACM (flagship publication of the ACM). Continue reading Social bot research featured on CACM, IEEE Computer covers

CASCI alumnus makes Fast Company’s most creative list

Dr. Ahmed Abdeen Hamed

Congratulations to CASCI alumnus Dr. Ahmed Abdeen Hamed who was recognized by FastCompany magazine, among the most creative people in the world, in 2016, for his research publication entitled: Twitter K-H networks in action: Advancing biomedical literature for drug search.Dr. Hamed completed his Computer Science MS degree at Indiana University in May 2005 and joined our Complex Networks & Systems track of the PhD in Informatics in the Fall of 2008. For personal reasons, he finished his PhD at the University of Vermont, but started his research in biomedical text mining with the CASCI group.

NaN represented, recognized at SoIC Spring Research Symposium

On Tuesday, April 19, IU School of Informatics and Computing hosted its Spring Research Symposium, where NaN was represented by two undergraduate research projects mentored by PhD candidate Clayton A Davis. Keychul Chung received 2nd prize honors for his work on a browser-based tool to compare historical trends of Twitter hashtag use. Kibeom Alex Hong presented a web-based tool to visualize geospatial trends in Twitter hashtag distribution over time. Both projects will be available as part of the Social Media Observatory tools to be released in early May.

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Talk by Ricardo Baeza-Yates: Data and Algorithmic Bias in the Web

Ricardo Baeza-YatesSpeaker: Ricardo Baeza-Yates, Universitat Pompeu Fabra, Spain & Universidad de Chile
Title: Data and Algorithmic Bias in the Web
Date: 04/22/2016
Time: 9am
Room: Info East 122
Abstract: The Web is the largest public big data repository that humankind has created. In this overwhelming data ocean we need to be aware of the quality and in particular, of biases that exist in this data, such as redundancy, spam, etc. These biases affect the algorithms that we design to improve the user experience. This problem is further exacerbated by biases that are added by these algorithms, especially in the context of search and recommendation systems. They include ranking bias, presentation bias, position bias, etc. We give several examples and their relation to sparsity, novelty, and privacy, stressing the importance of the user context to avoid these biases.
Bio: Ricardo Baeza-Yates areas of expertise are information retrieval, web search and data mining, data science and algorithms. He was VP of Research at Yahoo Labs, based in Barcelona, Spain, and later in Sunnyvale, California, from January 2006 to February 2016. He is part time Professor at DTIC of the Universitat Pompeu Fabra, in Barcelona, Spain. Until 2004 he was Professor and founding director of the Center for Web Research at the Dept. of Computing Science of the University of Chile. He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley in 2011 (2nd ed), that won the ASIST 2012 Book of the Year award. From 2002 to 2004 he was elected to the board of governors of the IEEE Computer Society and in 2012 he was elected for the ACM Council. Since 2010 is a founding member of the Chilean Academy of Engineering. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow, among other awards and distinctions.

Control of Complex Networks

Control of the eukaryotic cell cycle of budding yeast Saccharomyces cerevisiae (from, click for details)

Network science has allowed us to understand the organization of complex systems across disciplines. However, there is a need to understand how to control them; for example, to identify strategies to revert a diseased cell to a healthy state in cancer treatment. Recent work in the field—based on linear control theory—suggests that the controllability of complex systems can be predicted solely from the graph of interactions between variables, without considering their dynamics. Such graph-based approaches have been used, for instance, to suggest that biological systems are harder to control and have appreciably different control profiles than social or technological systems. The methodology has also been increasingly used in many applications from financial to biochemical networks.

In work published today in Nature Scientific Reports, CNetS graduate student Alexander Gates and Professor Luis Rocha demonstrate that such graph-based methods fail to characterize controllability when dynamics are introduced. The study computed the control profiles of large ensembles of multivariate systems as well as existing Systems Biology models of biochemical regulation in various organisms.

Continue reading Control of Complex Networks

Artemy Kolchinsky, recent Postdoc at the Santa Fe Institute

Artemy Kolchinsky
Artemy Kolchinsky

Recent CASCI Complex Systems & Networks Phd program graduate Artemy Kolchinsky, is now a postdoc at the Santa Fe Institute. While at SFI, Kolchinsky is working with “David Wolpert on several projects related to optimal use of information and prediction. One is the problem of modeling and analyzing complicated dynamical systems that require large amounts of time and computational power to simulate. […] Another project investigates connections
between information processing and statistical physics. […] The two are [also] beginning to work on understanding why different social groups develop different organizations, whether the group is a prehistoric tribe or a business firm.” More details on the SFI update newsletter.