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Kim, Lanu, Sanne Smith, Linus Dahlander and Daniel A. McFarland. Forthcoming. “Networking a Career: Individual Adaptation in the Network Ecology of Faculty.” Social Networks


LiCausi, Taylor, Daniel A. McFarland. 2022. “Abstract(s) at the Core: A Case Study of Disciplinary Identity in the Field of Linguistics." Higher Education

Hofstra, Bas, Sanne Smith, David Jurgens, and Daniel A. McFarland. 2022. “Diversifying the Professoriate.” Socius, Volume 8: 1– 26.

Risi, Stephan, Mathias W. Nielsen, Emma Kerr, Emer Brady, Lanu Kim, Daniel A. McFarland, Dan Jurafsky, James Zou, Londa Schiebinger. 2022. “Diversifying history: A large-scale analysis of changes in researcher demographics and scholarly agendas.” PLOS ONE 17(1): e0262027.

Kim, Lanu, Daniel Scott Smith, Bas Hofstra, Daniel A. McFarland. 2022. “Gendered Knowledge in Fields and Academic Careers.” Research Policy 51, 1: 104411.


Heiberger, Raphael, Sebastian Munoz-Najar Galvez, and Daniel A. McFarland. 2021. “Facets of Specialization and Its Relation to Career Success: An Analysis of U.S Sociology, 1980-2015.” American Sociological Review Vol. 86, 6: 1164–1192.

McFarland, Daniel A., Saurabh Khanna, Ben Domingue, Zachary Pardos. 2021. “Education Data Science: Past, Present, Future.” AERA Open 7, 1:1–12.

McMahan, Peter and Daniel A. McFarland. 2021. “Creative Destruction: The structural consequences of scientific curation.” American Sociological Review86(2), 341-376.


Stark, Tobias H., J. Ashwin Rambaran and Daniel A. McFarland. 2020. “The Meeting of the Minds: Forging Social and Intellectual Networks within Universities.” Sociological Science 7: 433-464.

Hofstra, Bas, Vivek V. Kulkarni, Sebastian Munoz-Najar Galvez, Bryan He, Dan Jurafsky, and Daniel A. McFarland. 2020. "The Diversity–Innovation Paradox in Science." Proceedings of the National Academy of Sciences 117, no. 17 (2020): 9284-9291.

Mäkinen, Elina I., Eliza D. Evans, & Daniel A. McFarland.  2020. “The Patterning of Collaborative Behavior and Knowledge Culminations in Interdisciplinary Research Centers.” Minerva 58: 71–95.


Munoz-Najar Galvez, Sebastian, Raphael Heiberger, & Daniel A. McFarland. 2019. “Paradigm Wars Revisited: A Cartography of Graduate Research in the Field of Education (1980–2010).” American Educational Research Journal 57(2): 612-52.


Biancani, Susan, Linus Dahlander, Daniel A. McFarland, and Sanne Smith. 2018.  “Superstars in the Making? The Broad Effects of Interdisciplinary Centers.” Research Policy 47: 543–557.

Jurgens, David, Srijan Kumar, Raine Hoover, Daniel A. McFarland, Dan Jurafsky. 2018. “Measuring the Evolution of a Scientific Field through Citation Frames.” Transactions of the Association for Computational Linguistics (TACL). 


Kim, Minkyoung, Daniel A. McFarland and Jure Leskovec. 2017. “Modeling Afinity based Popularity Dynamics.” CIKM’17, Singapore. DOI: 10.475/123 4 (20% acceptance)


Evans, Eliza D., Charles J. Gomez, and Daniel A. McFarland. 2016. “Measuring Paradigmaticness of Disciplines Using Text.” Sociological Science 3: 757-778.a  DOI: 10.15195/v3.a32

Prabhakaran, Vinodkumar, William Hamilton, Daniel A. McFarland, Dan Jurafsky. 2016. Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing.   Association for Computational Linguistics (ACL, 2016).cd

Smith, Sanne, Daniel A. McFarland, Frank van Tubergen & Ineke Maas. 2016. “Ethnic Composition and Friendship Segregation: Differential Effects for Adolescent Natives and Immigrants.” American Journal of Sociology 121(4): 1223-72.


McFarland, Daniel A., and H. Richard McFarland. 2015. "Big Data and the danger of being precisely inaccurate." Big Data & Society 2(2): DOI 2053951715602495.

McFarland, Daniel A., Kevin Lewis and Amir Goldberg. 2015. "Sociology in the Era of Big Data: The Ascent of Forensic Social Science.” American Sociologist, pp. 1-24.

Rawlings, Craig M., Daniel A. McFarland, Linus P. Dahlander, and Daniel J. Wang. 2015. “Streams of Thought: How Ties Form and Influence Flows among New Faculty.” Social Forces 93(4): 1687-1722.


McFarland, Daniel A., James Moody, David Diehl, Jeff Smith, and Reuben J. Thomas. 2014. “Network Ecology and Adolescent Social Structure.” American Sociological Review 79(6):

Biancani, Susan, Linus Dahlander, and Daniel A. McFarland. 2014. “The Semi-Formal Organization.” Organization Science 25(5): 1306-1324.ab 

Kizilcec, René, Emily Schneider, Geoffrey Cohen and Daniel A. McFarland. 2014. “Encouraging Forum Participation in Online Courses with Collectivist, Individualist, and Neutral Motivational Framings.” eLearning Papers, vol 37. 

Aiello, Lucca M. and Daniel A. McFarland. 2014. Social Informatics: Proceedings of the 6th International Conference (SocInfo 2014)


Biancani, Susan and Daniel A. McFarland.  2013. “Social Networks Research in Higher Education.” Higher Education: Handbook of Theory and Research 28: 151-215.

Chuang, Jason, Yuening Hu, Ashley Jin, John D Wilkerson, Daniel A McFarland, Christopher D Manning, Jeffrey Heer. 2013. “Document Exploration with Topic Modeling: Designing Interactive Visualizations to Support Effective Analysis Workflows.” Neural Information Processing Systems (NIPS), Workshop on Topic Models.

Dahlander, Linus and Daniel A. McFarland. 2013. “Ties that Last: A Longitudinal Study of Tie Formation and Persistence.” Administrative Science Quarterly 58 (1)69–110.

DuBois, Christopher, Carter T Butts, Daniel A McFarland and Padhraic Smyth. 2013. “Hierarchical Models for Relational Event Sequences.” Journal of Mathematical Psychology 57, 6:297–309.

McFarland, Daniel A., Christopher D. Manning, Daniel Ramage, Jason Chuang, Jeffrey Heer, and Dan Jurafsky. 2013. “Differentiating Language Usage Through Topic Models.” Poetics 41, 6:607–


Anderson, Ashton, Daniel A. McFarland, and Dan Jurafsky. 2012. “Towards a Computational History of the ACL: 1980-2008.” (ACL Workshop 2012).

Chuang, Jason, Christopher D. Manning, Jeffrey Heer. 2012. “Termite: Visualization Techniques for Assessing Textual Topic Models.” Proc. Advanced Visual Interfaces.

Chuang, Jason, Daniel Ramage, Christopher D. Manning, Jeffrey Heer. 2012. “Interpretation and Trust: Designing Model-Driven Visualizations for Text Analysis.” Proc. ACM Human Factors in Computing Systems (CHI).

Chuang, Jason, Daniel Ramage, Daniel A. McFarland, Christopher D. Manning and Jeffrey Heer. 2012. “Large-Scale Examination of Academic Publications Using Statistical Models.” Advanced Visual Interfaces Workshop (AVI Workshop).

Levin, Michale, Stefan Krawczyk, Steven Bethard, and Dan Jurafsky. 2012. “Citation-based bootstrapping for large-scale author disambiguation.” Journal of the American Society for Information Science and Technology, 63(5):1030-1047.

Stevenson, David K., Gary M. Shaw, Paul H. Wise, Mary E. Norton, Maurice L. Druzin and Daniel A. McFarland. 2012. “Transdisciplinary Translational Science and The Case of Preterm Birth.” The Journal of Perinatology (2012): 1-8.

Wang, Dan J., Xiaolin Shi, Daniel A. McFarland, and Jure Leskovec. 2012. "Measurement error in social network data: A re-classification." Social Networks. July, 34 (4).


Gupta, Sonal, and Christopher D. Manning. Analyzing the Dynamics of Research by Extracting Key Aspects of Scientific Papers.  In Proceedings of the International Joint Conference on Natural Language Processing (IJCNLP), 2011

Johri, N., D. Ramage, D. McFarland and D. Jurafsky. 2011. “A Study of Academic Collaboration in Computational Linguistics with Latent Mixtures of Authors.” Association of Computational Linguistics, Workshop (ACL Workshop 2011).

Nallapati, R., D. McFarland & C. Manning. 2011. TopicFlow Model: Unsupervised Learning of Topic-specific Influences of Hyperlinked Documents. Artificial Intelligence and Statistics  (AISTATS).

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).

Ramage, D. 2011. Studying People, Place, and the Web with Statistical Text Models. Doctoral thesis in computer science, Stanford University.

Ramage, Daniel, Christopher D. Manning, Susan Dumais. 2011. Partially Labeled Topic Models for Interpretable Text Mining. KDD 2011.

Rawlings, Craig and Daniel A. McFarland. 2011. “The Ties that Influence: How Social Networks Channel Faculty Grant Productivity.” Social Science Research 40: 1001-17.


Bethard, S. & D. Jurafsky. “Who Should I Cite? Learning Literature Search Models from Citation Behavior. International Conference on Information and Knowledge Management 2010.

Gupta, Sonal, and Christopher D. Manning. Identifying Focus, Techniques and Domain of Scientific Papers. NIPS workshop on Computational Social Science and the Wisdom of Crowds (NIPS-CSS), 2010

Krawczyk, S. 2010. Semi-supervised Learning For Author Disambiguation in Bibliographic Data. Master’s thesis in computer science, Stanford University.

Nallapati, R. & C. Manning. 2010. TopicFlow model: Unsupervised learning of topic specific influences of hyperlinked documents. Neural Information Processing Systems, Workshop (NIPS Workshop).

Ramage, D., D. McFarland & C. Manning. 2010. Which universities lead and lag? Toward university rankings based on scholarly output. Neural Information Processing Systems, Workshop (NIPS Workshop).

Shi, X., J. Leskovec & D. McFarland. 2010. Citing for High Impact. Joint Conference on Digital Libraries (JCDL).

Shi, X., R. Nallapati, J. Leskovec, D. McFarland & D. Jurafsky. 2010. Who Leads Whom: Topical Lead-Lag Analysis across Corpora. Neural Information Processing Systems, Workshop (NIPS Workshop).


Ch­uang, J, D. Ramage, J. Heer, & C. Manning. 2009. Thesis Topic Explorer.

Ramage, D., D. Hall, R. Nallapati & C. Manning. 2009. Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora. Empirical Methods in Natural Language Processing (EMNLP).

Ramage, D., E. Rosen, J. Chuang, C. Manning & D. McFarland. 2009. Topic Modeling for the Social Sciences. Neural Information Processing Systems, Workshop (NIPS Workshop).


Hall, D., D. Jurafsky, & C. Manning. 2008. Studying the History of Ideas Using Topic Models. Empirical Methods in Natural Language Processing (EMNLP).