Among the millions of real people tweeting about the presidential race, there are also a lot accounts operated by fake people, or “bots.” Politicians and regular users alike use these accounts to increase their follower bases and push messages. PBS NewsHour science correspondent Miles O’Brien reports on how CNetS computer scientists can analyze Twitter handles to determine whether or not they are bots.
Sponsored by Persistent Systems. Luis Rocha, Director of the Complex Systems PhD track in the School of Information and Computing at Indiana University Bloomington, explains the new software-driven approach to medical research. Big data generated through social media such as Twitter and Instragram provides a far deeper and fuller examination of the impact of medicines and diseases, leading to greater actionable insights to improve the efficacy of prevention and treatment.
Congratulations to Emilio Ferrara for winning the 2016 Junior Scientific Award from the Complex Systems Society (CCS), which unveiled the winners of the CSS scientific awards in a packed plenary session at ECCS’16 in Amsterdam, the Netherlands. Continue reading Emilio Ferrara receives Junior Scientific Award at CSS’16
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.
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