COSMOS is pushing the boundaries of information behavior research with its new publication about the dark side of information operations, which is the negative phenomenon associated with the management of information in the online environment. In the journal article “Combining advanced computational social science and graph theoretic techniques to reveal adversarial information operations” doctoral students Mustafa Alassad and Billy Spann and COSMOS director Dr. Nitin Agarwal introduce a method to identify malicious behavior and the actors responsible for propagating this behavior via online social networks. The researchers presented advanced socio-technical methods such as deviant cyber flash mob (DCFM) detection and focal structure analysis (FSA) that can provide reconnaissance capabilities for cities and governments to look beyond internal data and identify threats based on active events.
Dr. Agarwal, Maulden-Entergy Chair and Distinguished professor of Information science said, “This is a groundbreaking interdisciplinary work that combines operations research, social science, and computational science disciplines to tackle the real world problem of misinformation plaguing our society in numerous ways.”
“We are developing new scientific methods to understand how information spreads through social networks and what type of social network structures spread information most easily,” stated Billy Spann. “Bad actors take advantage of these network structures to coordinate different types of information operations, such as disinformation campaigns or deviant cyber flash mobs. The techniques used in this study will help us to identify the most influential users at the center of these information operations.”
The researchers examined multiple data sets integrating the DCFM and FSA models to help cybersecurity experts to gain better insights of threats that will help to plan a better response. Current studies on this topic are still limited, leaving considerable gaps in the literature, particularly on how to conceptualize and operationalize the dark or unexpected negative sides of online information behaviors, how to theorize the underlying cognitive, psychological, and social processes of such behaviors, and how to implement system design and information recognition to avoid negative information behaviors. Their work was published in the reputable, International Journal of Information Processing and Management by Elsevier. The full text of the publication is available at https://doi.org/10.1016/j.ipm.2020.102385.
This research is funded in part by the U.S. National Science Foundation, U.S. Office of Naval Research, U.S. Air Force Research Lab, U.S. Army Research Office, U.S. Defense Advanced Research Projects Agency, Arkansas Research Alliance, and the Jerry L. Maulden/Entergy Endowment at the University of Arkansas at Little Rock. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding organizations. The researchers gratefully acknowledge the support.