Research 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
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.
Did more people see #thedress as blue and black or white and gold? How many Twitter users wanted pop star Katy Perry to take the #icebucketchallenge? The power to explore online social media movements — from the pop cultural to the political — with the same algorithmic sophistication as top experts in the field is now available to journalists, researchers and members of the public from a free, user-friendly online software suite released today by scientists at Indiana University. The Web-based tools, called the Observatory on Social Media, or “OSoMe” (pronounced “awesome”), provide anyone with an Internet connection the power to analyze online trends, memes and other online bursts of viral activity. An academic pre-print paper on the tools is available in the open-access journal PeerJ.
“This software and data mark a major goal in our work on Internet memes and trends over the past six years,” said Filippo Menczer, director of the Center for Complex Networks and Systems Research and a professor in the IU School of Informatics and Computing. “We are beginning to learn how information spreads in social networks, what causes a meme to go viral and what factors affect the long-term survival of misinformation online. The observatory provides an easy way to access these insights from a large, multi-year dataset.” Read more.
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.
Speaker: Ricardo Baeza-Yates, Universitat Pompeu Fabra, Spain & Universidad de Chile
Title: Data and Algorithmic Bias in the Web
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.
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.
Congratulations to Clayton Davis, who won the best presenter prize at WWW 2016 Developers Day! Clayton presented BotOrNot: A system to evaluate social bots, a paper coauthored with Onur Varol, Emilio Ferrara, Alessandro Flammini and Filippo Menczer, that describes our latest API developments with the BotOrNot system.
The Center for Complex Networks and Systems Research (CNetS.indiana.edu), jointly with the Indiana University Network Science Institute (IUNI.iu.edu), has
two three open postdoctoral positions, two on the characterization and modeling of complex systems and one to study critical processes in networks of networks. The appointments start in Summer/Fall 2016 for one year and are renewable for one or two additional years, subject to funding and performance. The salary is competitive and benefits are generous.
The postdocs will join a dynamic and interdisciplinary team that includes computer, physical, and cognitive scientists. Two postdocs will work with Prof. Santo Fortunato on various areas of complex systems research, including community detection in networks, computational social science (opinion dynamics, online experiments on social influence) and science of science (citation and collaboration patterns between scientists, impact dynamics). A third postdoc will work with Prof. Filippo Radicchi. Continue reading Three postdoc positions in complex networks and systems
In an interview aired on the ABC (Australian) evening news program “The World” on April 4, 2016, Filippo Menczer discussed with host Beverley O’Connor how information and misinformation spread throughout the Internet and the roles of network structure and social bubbles in determining meme virality. Video here.
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.