Biography

I’m a PhD student in the Computer Science Department at Northern Illinois University, working with Dr. Hamed Alhoori and the DATA Lab. My research lies at the intersection of computational social science, data science, and the science of science.

In my Master’s work, I developed machine learning models to predict and measure the societal impact of research—going beyond traditional citation-based metrics—to include factors like policy citations, newsworthiness, and public understanding of scientific work.

My broader interests include text mining, social media analytics, altmetrics, and building interpretable models that reveal how research propagates and is understood by various audiences. I’ve co-authored studies such as “Using Social Media and Scholarly Text to Predict Public Understanding of Science” and “Assessment of Societal Impact of Research.”

I’m passionate about creating computational methods that help bridge the gap between scholarly outputs and public engagement, enabling better evaluation of scientific contributions in societal contexts.

Publications

  • Kale, B., Siravuri, H. V., Alhoori, H., & Papka, M. E. (2017, June). Predicting research that will be cited in policy documents. In Proceedings of the 2017 ACM on Web Science Conference (pp. 389-390).
  • Siravuri, H. V., Akella, A. P., Bailey, C., & Alhoori, H. (2018, May). Using social media and scholarly text to predict public understanding of science. In Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 385-386).
  • Siravuri, H. V., & Alhoori, H. (2017). What makes a research article newsworthy?. Proceedings of the Association for Information Science and Technology, 54(1), 802-803.
  • Bailey, C., Kale, B., Walker, J., Siravuri, H. V., Alhoori, H., & Papka, M. E. (2017, June). Exploring features for predicting policy citations. In 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL) (pp. 1-2). IEEE.