The Mimir Project Page: What Drives the Dynamics of Science?

Overview

Our multidisciplinary project draws upon sociology, computer science, and linguistics to study how ideas are created and propagate through scientific communities, how these communities are formed and change over time, and how multidisciplinary networks spanning these communities shape scientific innovation. We are creating sophisticated new computational models for extracting and representing ideas and measuring their impact and novelty, and for extracting and representing social relations and identifying forms of multidisciplinary collaboration. Our methods integrate the network analytic tools of social science with the language processing tools of computer science. We use network analysis to improve the ability of computational tools to identify ideas in scientific texts, and we use the tools of computational linguistics to help explain the co-evolution of scientific collaborations and innovations. We are using our models of ideas and their diffusion to investigate hypotheses such as whether multidisciplinary research accelerates or decelerates scientific innovation, and how multidisciplinarity influences student and faculty careers. We combine a shallow large-scale study of knowledge corpora (ISI Web of Knowledge, Proquest dissertations, NSF/NIH grants, US Patent Office, Federal committees) with a richer organization-level study of Stanford University (their publications, grants, affiliations, advising, teaching, etc) in order to explore and analyze the complex interrelationships of innovation and multidisciplinary collaboration.

Our research agenda is to produce new and unique data, create new computational tools, and extend theory so that scholars change their conceptions of scientific innovation, multidisciplinarity, and research communities more generally. Our integration of social network and natural language processing techniques is helping develop a new vein of research in computational social science, simultaneously offering empirical rigor and scale to the sociology of science and extending natural language processing from its previous engineering focus toward true explanatory social science models.

People

• Professors:
  • Daniel Jurafsky
  • Christopher Manning
  • Dan McFarland
  • Woody Powell
• Post-Docs and Research Associates
  • Ramesh Nallapati
  • Craig Rawlings
  • Xiaolin Shi
• Students:
  • Susan Biancani
  • Jason Chuang
  • Sasha Goodman
  • Sonal Gupta
  • Lindsay Owens
  • Daniel Ramage
  • Kaisa Snellman
  • Dan Wang
• Alums:
  • Steven Bethard
  • Linus Dahlander
  • David Hall
  • Stefan Krawczyk
  • Michael Levin

More information

You can find more and more up to date information at this site:

https://www.stanford.edu/dept/SUSE/cgi-bin/drupal/mimir/

Software

The Stanford Topic Modeling Toolbox

Papers

• Nallapati, R., X. Shi, D. McFarland, J. Leskovec & D. Jurafsky. 2011. LeadLag LDA: Estimating Topic Specific Leads and Lags of Information Outlets. International AAAI Conference on Weblogs and Social Media (ICWSM).
• Rawlings, C. & D. McFarland. 2011. "The Ties that Influence: How Social Networks Channel Faculty Grant Productivity." Social Science Research.
• Chuang, J, D. Ramage, J. Heer, & C. Manning. 2009. Thesis Explorer.
• Krawczyk, S. 2010. Semi-supervised Learning For Author Disambiguation in Bibliographic Data. Master's thesis in computer science, Stanford University.
• Nallapati, R., D. McFarland & C. Manning. 2011. TopicFlow Model: Unsupervised Learning of Topic-specific Influences of Hyperlinked Documents. Artificial Intelligence and Statistics (AISTATS).
• Xiaolin Shi, Ramesh Nallapati, Jure Lescovec, Dan McFarland and Dan Jurafsky. 2010. Who Leads Whom: Topical Lead-Lag analysis across corpora. NIPS Workshop on Computational Social Science and Wisdom of Crowds.
• Daniel Ramage, Christopher D. Manning, and Daniel A. McFarland. 2010. Which universities lead and lag? Toward university rankings based on scholarly output. NIPS 2010 Workshop on Computational Social Science and the Wisdom of the Crowds.
• Xiaolin Shi, Jure Leskovec, Daniel A. McFarland. 2010. Citing for High Impact. Joint Conference on Digital Libraries (JCDL), 2010.
• Steven Bethard and Dan Jurafsky. 2010. Who should I cite? Learning literature search models from citation behavior. In ACM Conference on Information and Knowledge Management. [PDF]
• Ramesh Nallapati and Christopher Manning. 2010. TopicFlow model: Unsupervised learning of topic specific influences of hyperlinked documents. Neural Information Processing Systems Workshop on Machine Learning for Social Computing.
• Daniel Ramage, Evan Rosen, Jason Chuang, Christopher D. Manning and Daniel A. McFarland. 2010. Topic Modeling for the Social Sciences. NIPS 2009 Workshop on Applications for Topic Models.
• Daniel Ramage, David Hall, Ramesh Nallapati, and Christopher Manning. 2009. Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora. EMNLP 2009
• Chuang, Jason, Daniel Ramage, Jeff Heer, and Christopher Manning. 2009. Thesis Topic Explorer. http://graphics.stanford.edu/~jcchuang/thesis-explorer/
• Daniel Ramage, Evan Rosen, Jason Chuang, Christopher D. Manning, and Daniel A. McFarland. 2009. Topic Modeling for the Social Sciences. In NIPS 2009 Workshop on Applications for Topic Models: Text and Beyond. [pdf, bib]
• David LW Hall, Daniel Jurafsky, and Christopher D. Manning. 2008. Using Topic Models to Study the History of Ideas. EMNLP 2008

Conference Presentations

• Biancani, Susan, Daniel A. McFarland, Linus Dahlander and Lindsay Owens. Extending Intellectual Communities: How Interdisciplinary Centers Extend Traditional Disciplinary Associations. Presented at Association for the Study of Higher Education in November 2009.
• Dahlander, Linus and Daniel McFarland. 2009b. Intellectual Tie Formation: Multiple Networks and Refunctionality. Presented at the annual SUNBELT meeting of the International Network for Network Analysis (April 2009) and the Academy of Management in August 2009.
• Rawlings, Craig and Daniel McFarland. The Ties That Influence. Presented at the annual SUNBELT meeting of the International Network for Network Analysis (April 2009).
• Rawlings, Craig, Linus Dahlander, Dan Wang, and Daniel McFarland. Contemporary Forms of the Academic Life: Social Structure and Knowledge Structure in 74 University Departments, 1993 to 2007. Presented at Association for the Study of Higher Education in November 2009.

Testset Collection

If you have papers that are contained in the ISI Web of Knowledge, please consider providing your publication information to help us match authors to publications.