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.
The IEEE Spectrum piece Real-Time Search Stumbles Out of the Gate discusses the recent integration of real-time search features, such as Twitter and other microblog entries, into major search engines. Professor Filippo Menczer, CNetS associate director, comments in the article on the challenges posed by real-time search. Here is an excerpt of the interview:
IU’s Menczer suggests that with all this user-generated content, the environment is more complex than the one Google’s PageRank algorithm had to deal with. While search used to be about relationships between pages, he explains, now it’s about relationships between ”people, tags, Web pages, ratings, votes, and direct social links….It may not be that page A points to page B but rather that user John follows Mary and replies to the tweet of Jane and retweets it.” That makes it ”a more complicated ecosystem,” he says, ”but a very rich one,” and search engines will need ”more sophisticated ways to extract data from these relationships” […]
This sabbatical is providing wonderful opportunities for me to present our work and establish/strengthen collaborations with several groups in Italy. Recently I have given invited seminars on social search at the Department of Informatics at the University of Torino (hosts Matteo Sereno and Mino Anglano) and on Web traffic at the Department of Math at the University of Padova (host Massimo Marchiori). In the next few weeks I will give a talk on social search at the Department of Informatics and Information Science at the University of Genova (host Marina Ribaudo) and one on search engine bias and Web modeling at my old stomping ground, the Institute of Cognitive Sciences and Technologies of the National Research Council in Rome (host my undergraduate advisor and mentor Domenico Parisi).
I just got back from a visit to Yahoo! Research Silicon Valley. I gave two talks presenting our work on social search and web traffic analysis, and met lots of interesting people. They have an amazing group and of course mountains of data to lust after. Hopefully this will lead to collaborations in the future, given the many intersecting research interests.
I will give a talk on social search at the Workshop on Social Data Mining and Knowledge Building, part III of the Mathematics of Knowledge and Search Engines program. The workshop, organized by IPAM, will be held 5–9 November 2007 at UCLA. Joining me as speakers are Luis Rocha and Stan Wasserman from IU and Santo Fortunato and Jose Ramasco from ISI/CNLL. Should be fun!
Building Better Search Engines by Pam Frost Gorder in Computing in Science and Engineering, vol. 9, no. 4, pp. 7-11, Jul/Aug 2007