Congratulations to Rion Correia, who successfully defended his PhD dissertation on Prediction of Drug Interaction and Adverse Reactions, with data from Electronic Health Records, Clinical Reporting, Scientific Literature, and Social Media, using Complexity Science Methods. Dr. Correia’s research used network science, machine learning, and data science to uncover population-level associations of drugs and symptoms, useful for public health surveillance. His findings show that Social Media (Instagram and Twitter) and Electronic Health Records of an entire city in Southern Brazil, are very useful to reveal how the Drug interaction phenomenon varies across distinct groups. For instance, he identifying gender biases and specific communities of interest in chronic disease (e.g. Epilepsy and Depression). In addition to Complex Networks and Systems, his dissertation contributes to the fields of biomedical informatics and precision public health by leveraging heterogeneous data sources at multiple levels to understand population and individual pharmacology differences and other public health problems.
Congratulations to Dimitar Nikolov, who successfully defended his PhD dissertation on Information Exposure Biases in Online Behaviors. Dr. Nikolov’s research explored the unintentional biases introduced by filtering, ranking, and recommendation algorithms that mediate our online consumption of information. His findings show that our reliance on modern online technologies limits exposure to diverse points of view and makes us vulnerable to misinformation. In particular, he analyzed two massive Web traffic datasets to quantify the popularity and homogeneity bias of several popular online platforms including social media, email, personalized news, and search engines. He also leveraged Twitter data to characterize the link between political partisanship and vulnerability to online pollution, such as fake news, conspiracy theories, and junk science. His dissertation contributes to the field of computational social science by putting the study of bias in information consumption and derived phenomena like political polarization, echo chambers, and online pollution on a more firm quantitative foundation.
A new paper published in Nature Reviews Physics by Professor Santo Fortunato and colleagues from Northwestern University features a detailed analysis of the careers of Nobel Prize Laureates. They found that the prize- winning works in the three main science categories (physics, chemistry and medicine) tend to occur early in the career of the Laureate.
This may be due to a selection effect — because the Nobel Prize in science has never been awarded posthumously, those who produced groundbreaking works early on in their careers were more likely to wait long enough to be recognized. Also, award-winning papers tend to be produced by small teams, on average. Apart from the prize-winning work, which may be subject to peculiarities of the Nobel, there is no known major difference that distinguishes patterns governing the careers of scientific elites from those of ordinary scientists.
Alexander T. J. Barron, a PhD candidate in CNetS, and co-authors are recipients of the 2018 Cozzarelli Prize in Behavioral and Social Sciences for their paper, Individuals, institutions, and innovation in the debates of the French Revolution. Every year, six of these awards are given to PNAS publications according to their “outstanding scientific quality and originality.” Each of the papers selected were chosen from the more than 3,200 research articles that appeared in PNAS during the last year and represent the six broadly defined classes under which the National Academy of Sciences is organized. The paper is the product of an interdisciplinary research team across several universities: Alexander Barron (Informatics, IU), Simon DeDeo (Social and Decision Sciences, Carnegie Mellon and the Santa Fe Institute), Rebecca Spang (History, IU), and Jenny Huang (soon to be attending Oxford).Continue reading CNetS article wins PNAS Cozzarelli prize
Luis Rocha, Katy Borner, Paul Macklin and other faculty from the School of Informatics, Computing and Engineering (SICE) were the awardees of the 2019 SICE Research Awards. Luis Rocha received the award in recognition of the NSF Research Traineeship (NRT) on Complex Networks and Systems and two NIH NLM R01 grants. The awards were handed by SICE Dean Raj Acharya and Associate Dean for Research Kay Connelly.
CNetS Professor Luis Rocha, together with ISI foundation (ISI) scientist Ciro Cattuto organize a workshop with the Instituto Gulbenkian de Ciencia to explore synergies between data/computational science and the life, health and social sciences. More information on the workshop event page.Continue reading Charting interdisciplinary research opportunities between data and life sciences
Filippo Menczer, a professor of computer science and informatics at CNetS, appeared on a panel of experts to discuss the emergence and dissemination of misinformation, and how it threatens society at the annual meeting of American Association for the Advancement of Science in Washington, D.C., Feb. 15.
Menczer was a part of a three-person panel and presented a talk, “Eight Ways Social Media Makes Society Vulnerable to Misinformation.” The talk provided an overview of ongoing network analytics, modeling, and machine learning efforts to study the viral spread of misinformation and to develop tools for countering the online manipulation of opinions. Menczer has previously developed systems such as Botometer, which detects social media bots, and Hoaxy, which maps the diffusion of low-credibility content.Continue reading CNeTS researcher provides expertise on misinformation battle at AAAS conference
Your mother always told you that if something was bothering you, you should talk about it. It would make you feel better. Turns out she was right, and researchers at the School of Informatics, Computing, and Engineering have the science to prove it. Johan Bollen, a professor of informatics and computing, leads a team that analyzed the Twitter feeds of tens of thousands of users to study how emotions change before and after they were explicitly stated. In the study, “The minute-scale dynamics of online emotions reveal the effects of affect labeling,” published in the journal Nature Human Behaviour, Bollen and his colleagues used algorithms to measure how the positivity or negativity of tweets change before or after a user explicitly expressed having an emotion, e.g. saying “I feel bad” or “I feel good.” Their study not only reveals how emotions evolve over time, but also how their expression may change them, and how these changes differ between men and women.Continue reading CNetS social media study shows how affect labeling can help moderate emotions
The National Institutes of Health, under the National Library of Medicine’s program on data science research, awarded a $1.55 million grant to an interdisciplinary team lead by Luis Rocha, a professor of informatics, member of CNETS and the director of the NSF-NRT complex networks & systems program at the School of Informatics, Computing, and Engineering. The four-year project, a collaboration between SICE and the Indiana University School of Nursing, will employ innovative data- and network-science methods to produce myAURA, an easy-to-use web service for epilepsy patients. myAURA will be based on a large-scale epilepsy knowledge graph built by integrating data from social media, electronic health records, patient discussion boards, scientific literature databases, advocacy websites, and mobile app data. The knowledge graph will, in turn, be used to fuel recommendation and visualization algorithms based on the automatic inference of relevant associations. The inference will follow algorithms developed by Rocha’s team to remove redundancy and extract factual information from large knowledge graphs as well as parsimonious network visualizations developed by Katy Börner, Distinguished Professor of Engineering & Information Science at SICE. Continue reading CNetS team awarded NIH grant to improve chronic-disease management with Data and Network Science
Onur Varol, a postdoctoral research associate at Northeastern University who earned his Ph.D. in Informatics from CNetS, has been honored with the University Distinguished Ph.D. Dissertation Award for 2018, which is the highest honor for research Indiana University bestows on its graduate students. “I am extremely happy to receive this award,” Varol said. “I would like to especially thank my advisor, Filippo Menczer, and the Informatics department for nominating me. I was lucky to be surrounded by the best advisors, collaborators, and research group I could imagine during my doctoral studies, and I am a proud IU alumni and a Hoosier.” Varol’s dissertation, “Analyzing Social Big Data to Study Online Discourse and Its Manipulation,” provided insights into analysis of online conversations and mechanisms used for their manipulation. Varol built machine learning frameworks like Botometer to detect social bots. More…