Daniel McFarland

All Publications

• Coming into relations: How communication reveals and persuades relational decisions SOCIAL NETWORKS McFarland, D. A., Broska, D., Prabhakaran, V., Jurafsky, D. 2024; 79: 57-75

  View details for DOI 10.1016/j.socnet.2024.05.003

  View details for Web of Science ID 001258877300001

• Networking a career: Individual adaptation in the network ecology of faculty SOCIAL NETWORKS Kim, L., Smith, S., Dahlander, L., McFarland, D. A. 2024; 77: 166-179

  View details for DOI 10.1016/j.socnet.2022.04.002

  View details for Web of Science ID 001188389100001

• Network Ecology: Introduction to the Special Issue SOCIAL NETWORKS Doehne, M., Mcfarland, D. A., Moody, J. 2024; 77: 1-4

  View details for DOI 10.1016/j.socnet.2023.12.001

  View details for Web of Science ID 001188768500001

• Network ecology: Tie fitness in social context(s) SOCIAL NETWORKS Doehne, M., Mcfarland, D. A., Moody, J. 2024; 77: 180-196

  View details for DOI 10.1016/j.socnet.2023.11.002

  View details for Web of Science ID 001188643200001

• Interdisciplinary Research, Tenure Review, and Guardians of the Disciplinary Order JOURNAL OF HIGHER EDUCATION Makinen, E. I., Evans, E. D., McFarland, D. A. 2024

  View details for DOI 10.1080/00221546.2024.2301912

  View details for Web of Science ID 001144072400001

• Network ecology: Tie fitness in social context(s) SOCIAL NETWORKS Doehne, M., McFarland, D. A., Moody, J. 2024; 76: 174-190

  View details for DOI 10.1016/j.socnet.2023.09.005

  View details for Web of Science ID 001089067400001

• Network ecology: Tie fitness in social context(s). Social networks Doehne, M., McFarland, D. A., Moody, J. 2024; 76: 174-190

  Abstract

  Social relations are embedded in material, cultural, and institutional settings that affect network dynamics and the resulting topologies. For example, romantic entanglements are subject to social and cultural norms, interfirm alliances are constrained by country-specific legislation, and adolescent friendships are conditioned by classroom settings and neighborhood effects. In short, social contexts shape social relations and the networks they give rise to. However, how and when they do so remain to be established. This paper presents network ecology as a general framework for identifying how the proximal environment shapes social networks by focusing interactions and social relations, and how these interactions and relations in turn shape the environment in which social networks form. Tie fitness is introduced as a metric that quantifies how well particular dyadic social relations would align with the setting. Using longitudinal networks collected on two cohorts each in 18 North American schools, i.e., 36 settings, we develop five generalizable observations about the time-varying fitness of adolescent friendship. Across all 252 analyzed networks, tie fitness predicted new tie formation, tie longevity, and tie survival. Dormant fit ties cluster in relational niches, thereby establishing a resource base for social identities competing for increased representation in the relational system.

  View details for DOI 10.1016/j.socnet.2023.09.005

  View details for PubMedID 39006096

  View details for PubMedCentralID PMC11243588

• WHEN ERGMS LEAD TO BIASED SAMPLES: REPLY TO KRETSCHMER ET AL. AMERICAN JOURNAL OF SOCIOLOGY Smith, S., van Tubergen, F., Maas, I., Mcfarland, D. A. 2023; 129 (2): 586-602

  View details for DOI 10.1086/727858

  View details for Web of Science ID 001099877300007

• How New Ideas Diffuse in Science AMERICAN SOCIOLOGICAL REVIEW Cheng, M., Smith, D., Ren, X., Cao, H., Smith, S., McFarland, D. A. 2023

  View details for DOI 10.1177/00031224231166955

  View details for Web of Science ID 000978035500001

• Sociality and Elementary Forms of Structure NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 143-160

  View details for Web of Science ID 001062521000007

• Breaking Out of the Ivory Tower: A Large-scale Analysis of Patent Citations to HCI Research Cao, H., Lu, Y., Deng, Y., McFarland, D. A., Bernstein, M. S., ACM ASSOC COMPUTING MACHINERY. 2023

  View details for DOI 10.1145/3544548.3581108

  View details for Web of Science ID 001037809507029

• <i>Network Analysis Today</i> Introduction NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 1-+

  View details for Web of Science ID 001062521000001

• Positions and Roles NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 216-245

  View details for Web of Science ID 001062521000010

• Cohesion and Groups NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 161-189

  View details for Web of Science ID 001062521000008

• Hierarchy and Centrality NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 190-215

  View details for Web of Science ID 001062521000009

• How Are Social Network Data Collected? NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 67-87

  View details for Web of Science ID 001062521000004

• Models for Social Influence NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 364-389

  View details for Web of Science ID 001062521000015

• Network Analysis NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., McFarland, D. A. 2023: 1-455

  View details for DOI 10.1017/9781139794985

  View details for Web of Science ID 001062521000017

• What Is Social Structure? NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 19-44

  View details for Web of Science ID 001062521000002

• Structuration and Egocentric Networks NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 117-142

  View details for Web of Science ID 001062521000006

• Models for Network Diffusion NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 340-363

  View details for Web of Science ID 001062521000014

• Networks and Culture NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 269-298

  View details for Web of Science ID 001062521000012

• How Are Social Network Data Visualized? NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 88-114

  View details for Web of Science ID 001062521000005

• Affiliations and Dualities NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 246-268

  View details for Web of Science ID 001062521000011

• What Is a Social Network? NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 45-66

  View details for Web of Science ID 001062521000003

• Models for Networks NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 301-339

  View details for Web of Science ID 001062521000013

• <i>Network Analysis Tomorrow</i> Conclusion NETWORK ANALYSIS Rawlings, C. M., Smith, J. A., Moody, J., Mcfarland, D. A., Rawlings, C., Smith, J., Moody, J., McFarland, D. 2023: 390-419

  View details for Web of Science ID 001062521000016

• Writing into relationships SOCIAL NETWORKS McFarland, D. A., Wolff, T. 2022; 71: 96-114

  View details for DOI 10.1016/j.socnet.2022.06.006

  View details for Web of Science ID 000932028700003

• Systematic analysis of 50 years of Stanford University technology transfer and commercialization. Patterns (New York, N.Y.) Liang, W., Elrod, S., McFarland, D. A., Zou, J. 2022; 3 (9): 100584

  Abstract

  This article systematically investigates the technology licensing by Stanford University. We analyzed all the inventions marketed by Stanford's Office of Technology Licensing (OTL) between 1970 to 2020, with 4,512 inventions from 6,557 inventors. We quantified how the innovation landscape at Stanford changed over time and examined factors that correlate with commercial success. We found that the most profitable inventions are predominantly licensed by inventors' own startups, inventions have involved larger teams over time, and the proportion of female inventors has tripled over the past 25 years. We also identified linguistic features in how the inventors and OTL describe the inventions that significantly correlate with the invention's future revenue. Interestingly, inventions with more adjectives in their abstracts have worse net income. Our study opens up a new perspective for analyzing the translation of research into practice and commercialization using large-scale computational and linguistics analysis.

  View details for DOI 10.1016/j.patter.2022.100584

  View details for PubMedID 36124300

• Abstract(s) at the core: a case study of disciplinary identity in the field of linguistics HIGHER EDUCATION LiCausi, T. J., McFarland, D. A. 2022

  View details for DOI 10.1007/s10734-021-00810-8

  View details for Web of Science ID 000784820100005

• Diversifying the Professoriate SOCIUS Hofstra, B., McFarland, D. A., Smith, S., Jurgens, D. 2022; 8

  View details for DOI 10.1177/23780231221085118

  View details for Web of Science ID 000846864100001

• Diversifying history: A large-scale analysis of changes in researcher demographics and scholarly agendas. PloS one Risi, S., Nielsen, M. W., Kerr, E., Brady, E., Kim, L., McFarland, D. A., Jurafsky, D., Zou, J., Schiebinger, L. 1800; 17 (1): e0262027

  Abstract

  BACKGROUND: In recent years, interest has grown in whether and to what extent demographic diversity sparks discovery and innovation in research. At the same time, topic modeling has been employed to discover differences in what women and men write about. This study engages these two strands of scholarship to explore associations between changing researcher demographics and research questions asked in the discipline of history. Specifically, we analyze developments in history as women entered the field.METHODS: We focus on author gender in diachronic analysis of history dissertations from 1980 (when online data is first available) to 2015 and a select set of general history journals from 1950 to 2015. We use correlated topic modeling and network visualizations to map developments in research agendas over time and to examine how women and men have contributed to these developments.RESULTS: Our summary snapshot of aggregate interests of women and men for the period 1950 to 2015 identifies new topics associated with women authors: gender and women's history, body history, family and households, consumption and consumerism, and sexuality. Diachronic analysis demonstrates that while women pioneered topics such as gender and women's history or the history of sexuality, these topics broaden over time to become methodological frameworks that historians widely embraced and that changed in interesting ways as men engaged with them. Our analysis of history dissertations surface correlations between advisor/advisee gender pairings and choice of dissertation topic.CONCLUSIONS: Overall, this quantitative longitudinal study suggests that the growth in women historians has coincided with the broadening of research agendas and an increased sensitivity to new topics and methodologies in the field.

  View details for DOI 10.1371/journal.pone.0262027

  View details for PubMedID 35045091

• Gendered knowledge in fields and academic careers RESEARCH POLICY Kim, L., Smith, D., Hofstra, B., McFarland, D. A. 2022; 51 (1)

  View details for DOI 10.1016/j.respol.2021.104411

  View details for Web of Science ID 000716138700002

• Facets of Specialization and Its Relation to Career Success: An Analysis of US Sociology, 1980 to 2015 AMERICAN SOCIOLOGICAL REVIEW Heiberger, R. H., Galvez, S., McFarland, D. A. 2021

  View details for DOI 10.1177/00031224211056267

  View details for Web of Science ID 000725673100001

• Education Data Science: Past, Present, Future AERA OPEN McFarland, D. A., Khanna, S., Domingue, B. W., Pardos, Z. A. 2021; 7

  View details for DOI 10.1177/23328584211052055

  View details for Web of Science ID 000710518100001

• Creative Destruction: The Structural Consequences of Scientific Curation AMERICAN SOCIOLOGICAL REVIEW McMahan, P., McFarland, D. A. 2021

  View details for DOI 10.1177/0003122421996323

  View details for Web of Science ID 000630564600001

• The Meeting of Minds: Forging Social and Intellectual Networks within Universities SOCIOLOGICAL SCIENCE Stark, T. H., Rambaran, J., McFarland, D. A. 2020; 7: 433–64

  View details for DOI 10.15195/v7.a18

  View details for Web of Science ID 000569767000001

• The Diversity-Innovation Paradox in Science. Proceedings of the National Academy of Sciences of the United States of America Hofstra, B., Kulkarni, V. V., Munoz-Najar Galvez, S., He, B., Jurafsky, D., McFarland, D. A. 2020

  Abstract

  Prior work finds a diversity paradox: Diversity breeds innovation, yet underrepresented groups that diversify organizations have less successful careers within them. Does the diversity paradox hold for scientists as well? We study this by utilizing a near-complete population of 1.2 million US doctoral recipients from 1977 to 2015 and following their careers into publishing and faculty positions. We use text analysis and machine learning to answer a series of questions: How do we detect scientific innovations? Are underrepresented groups more likely to generate scientific innovations? And are the innovations of underrepresented groups adopted and rewarded? Our analyses show that underrepresented groups produce higher rates of scientific novelty. However, their novel contributions are devalued and discounted: For example, novel contributions by gender and racial minorities are taken up by other scholars at lower rates than novel contributions by gender and racial majorities, and equally impactful contributions of gender and racial minorities are less likely to result in successful scientific careers than for majority groups. These results suggest there may be unwarranted reproduction of stratification in academic careers that discounts diversity's role in innovation and partly explains the underrepresentation of some groups in academia.

  View details for DOI 10.1073/pnas.1915378117

  View details for PubMedID 32291335

• The Patterning of Collaborative Behavior and Knowledge Culminations in Interdisciplinary Research Centers MINERVA Makinen, E. I., Evans, E. D., McFarland, D. A. 2020; 58 (1)

  View details for DOI 10.1007/s11024-019-09381-6

  View details for Web of Science ID 000517064000004

• Paradigm Wars Revisited: A Cartography of Graduate Research in the Field of Education (1980-2010) AMERICAN EDUCATIONAL RESEARCH JOURNAL Galvez, S., Heiberger, R., McFarland, D. 2019

  View details for DOI 10.3102/0002831219860511

  View details for Web of Science ID 000475014900001

• The Patterning of Collaborative Behavior and Knowledge Culminations in Interdisciplinary Research Centers Minerva Mäkinen, E. I., Evans, E. D., McFarland, D. A. 2019: 1-25
• Superstars in the making? The broad effects of interdisciplinary centers RESEARCH POLICY Biancani, S., Dahlander, L., McFarland, D. A., Smith, S. 2018; 47 (3): 543–57

  View details for DOI 10.1016/j.respol.2018.01.014

  View details for Web of Science ID 000427664000001

• Measuring the evolution of a scientific field through citation frames Transactions of the Association for Computational Linguistics Jurgens, D., Kumar, S., Hoover, R., McFarland, D., Jurafsky, D. 2018; 6: 391-406
• Modeling Affinity based Popularity Dynamics Kim, M., McFarland, D. A., Leskovec, J., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2017: 477–86

  View details for DOI 10.1145/3132847.3132923

  View details for Web of Science ID 000440845300048

• Descriptive Analysis in Education: A Guide for Researchers. NCEE 2017-4023. National Center for Education Evaluation and Regional Assistance Loeb, S., Dynarski, S., McFarland, D., Morris, P., Reardon, S., Reber, S. 2017
• Ethnic Composition and Friendship Segregation: Differential Effects for Adolescent Natives and Immigrants AMERICAN JOURNAL OF SOCIOLOGY Smith, S., van Tubergen, F., Maas, I., McFarland, D. A. 2016; 121 (4): 1223-1272

  Abstract

  Ethnically diverse settings provide opportunities for interethnic friendship but can also increase the preference for same-ethnic friendship. Therefore, same-ethnic friendship preferences, or ethnic homophily, can work at cross-purposes with policy recommendations to diversify ethnic representation in social settings. In order to effectively overcome ethnic segregation, we need to identify those factors within diverse settings that exacerbate the tendency toward ethnic homophily. Using unique data and multiple network analyses, the authors examine 529 adolescent friendship networks in English, German, Dutch, and Swedish schools and find that the ethnic composition of school classes relates differently to immigrant and native homophily. Immigrant homophily disproportionately increases as immigrants see more same-ethnic peers, and friendship density among natives has no effect on this. By contrast, native homophily remains relatively low until natives see dense groups of immigrants. The authors' results suggest that theories of interethnic competition and contact opportunities apply differently to ethnic majority and minority groups.

  View details for Web of Science ID 000369717400006

• Sociology in the era of big data: The ascent of forensic social science The American Sociologist McFarland, D. A., Lewis, K., Goldberg, A. 2016; 47 (1): 12-35
• Community (in) colleges: The relationship between online network involvement and academic outcomes at a community college Community College Review Evans, E. D., McFarland, D. A., Rios-Aguilar, C., Deil-Amen, R. 2016; 44 (3): 232-254
• Measuring paradigmaticness of disciplines using text Sociological Science Evans, E. D., Gomez, C. J., McFarland, D. A. 2016; 3: 757-778
• Citation classification for behavioral analysis of a scientific field arXiv preprint arXiv:1609.00435 Jurgens, D., Kumar, S., Hoover, R., McFarland, D., Jurafsky, D. 2016
• Streams of Thought: Knowledge Flows and Intellectual Cohesion in a Multidisciplinary Era SOCIAL FORCES Rawlings, C. M., McFarland, D. A., Dahlander, L., Wang, D. 2015; 93 (4): 1687-1722

  View details for DOI 10.1093/sf/sov004

  View details for Web of Science ID 000355663700044

• The Organization of Schools and Classrooms Emerging Trends in the Social and Behavioral Sciences: An Interdisciplinary, Searchable, and Linkable Resource Diehl, D., McFarland, D. A. 2015: 1-15
• Big data and the danger of being precisely inaccurate Big Data & Society McFarland, D. A., McFarland, R. 2015; 2 (2): 2053951715602495
• Social Informatics: SocInfo 2014 International Workshops, Barcelona, Spain, November 11, 2014, Revised Selected Papers Aiello, L. M., McFarland, D. Springer. 2015
• Network Ecology and Adolescent Social Structure AMERICAN SOCIOLOGICAL REVIEW McFarland, D. A., Moody, J., Diehl, D., Smith, J. A., Thomas, R. J. 2014; 79 (6): 1088-1121

  Abstract

  Adolescent societies-whether arising from weak, short-term classroom friendships or from close, long-term friendships-exhibit various levels of network clustering, segregation, and hierarchy. Some are rank-ordered caste systems and others are flat, cliquish worlds. Explaining the source of such structural variation remains a challenge, however, because global network features are generally treated as the agglomeration of micro-level tie-formation mechanisms, namely balance, homophily, and dominance. How do the same micro-mechanisms generate significant variation in global network structures? To answer this question we propose and test a network ecological theory that specifies the ways features of organizational environments moderate the expression of tie-formation processes, thereby generating variability in global network structures across settings. We develop this argument using longitudinal friendship data on schools (Add Health study) and classrooms (Classroom Engagement study), and by extending exponential random graph models to the study of multiple societies over time.

  View details for DOI 10.1177/0003122414554001

  View details for Web of Science ID 000345458400003

  View details for PubMedCentralID PMC4271807

• The Semiformal Organization ORGANIZATION SCIENCE Biancani, S., McFarland, D. A., Dahlander, L. 2014; 25 (5): 1306-1324

  View details for DOI 10.1287/orsc.2013.0882

  View details for Web of Science ID 000342281700002

• Encouraging Forum Participation in Online Courses with Collectivist, Individualist, and Neutral Motivational Framings. eLearning Papers Kizilcec, R., Schneider, E., Cohen, G., McFarland, D. A. 2014; 37
• The Semi-Formal Organization Organization Science, Permalink: http://dx.doi.org/10.1287/orsc.2013.0882 Biancani, S., Dahlander, L., McFarland, D. A. 2014
• Hierarchical models for relational event sequences JOURNAL OF MATHEMATICAL PSYCHOLOGY DuBois, C., Butts, C. T., Mcfarland, D., Smyth, P. 2013; 57 (6): 297-309

  View details for DOI 10.1016/j.jmp.2013.04.001

  View details for Web of Science ID 000328712300004

• Differentiating language usage through topic models POETICS McFarland, D. A., Ramage, D., Chuang, J., Heer, J., Manning, C. D., Jurafsky, D. 2013; 41 (6): 607-625

  View details for DOI 10.1016/j.poetic.2013.06.004

  View details for Web of Science ID 000329558200003

• Making the Connection: Social Bonding in Courtship Situations AMERICAN JOURNAL OF SOCIOLOGY McFarland, D. A., Jurafsky, D., Rawlings, C. 2013; 118 (6): 1596-1649

  View details for DOI 10.1086/670240

  View details for Web of Science ID 000321045300004

• Transdisciplinary translational science and the case of preterm birth JOURNAL OF PERINATOLOGY Stevenson, D. K., Shaw, G. M., Wise, P. H., Norton, M. E., Druzin, M. L., Valantine, H. A., McFarland, D. A. 2013; 33 (4): 251-258

  Abstract

  Medical researchers have called for new forms of translational science that can solve complex medical problems. Mainstream science has made complementary calls for heterogeneous teams of collaborators who conduct transdisciplinary research so as to solve complex social problems. Is transdisciplinary translational science what the medical community needs? What challenges must the medical community overcome to successfully implement this new form of translational science? This article makes several contributions. First, it clarifies the concept of transdisciplinary research and distinguishes it from other forms of collaboration. Second, it presents an example of a complex medical problem and a concrete effort to solve it through transdisciplinary collaboration: for example, the problem of preterm birth and the March of Dimes effort to form a transdisciplinary research center that synthesizes knowledge on it. The presentation of this example grounds discussion on new medical research models and reveals potential means by which they can be judged and evaluated. Third, this article identifies the challenges to forming transdisciplines and the practices that overcome them. Departments, universities and disciplines tend to form intellectual silos and adopt reductionist approaches. Forming a more integrated (or 'constructionist'), problem-based science reflective of transdisciplinary research requires the adoption of novel practices to overcome these obstacles.

  View details for DOI 10.1038/jp.2012.133

  View details for PubMedID 23079774

• Ties That Last: Tie Formation and Persistence in Research Collaborations over Time ADMINISTRATIVE SCIENCE QUARTERLY Dahlander, L., McFarland, D. A. 2013; 58 (1): 69-110

  View details for DOI 10.1177/0001839212474272

  View details for Web of Science ID 000318801100004

• Social Networks Research in Higher Education. Higher Education: Handbook of Theory and Research Biancani, S., McFarland, D. A. 2013; 28: 151-215
• Detecting friendly, flirtatious, awkward, and assertive speech in speed-dates COMPUTER SPEECH AND LANGUAGE Ranganath, R., Jurafsky, D., McFarland, D. A. 2013; 27 (1): 89-115

  View details for DOI 10.1016/j.csl.2012.01.005

  View details for Web of Science ID 000311524800006

• Measurement error in network data: A re-classification SOCIAL NETWORKS Wang, D. J., Shi, X., McFarland, D. A., Leskovec, J. 2012; 34 (4): 396-409

  View details for DOI 10.1016/j.socnet.2012.01.003

  View details for Web of Science ID 000313304100004

• Classroom Ordering and the Situational Imperatives of Routine and Ritual SOCIOLOGY OF EDUCATION Diehl, D., McFarland, D. A. 2012; 85 (4): 326-349

  View details for DOI 10.1177/0038040712452093

  View details for Web of Science ID 000309140200002

• Influence flows in the academy: Using affiliation networks to assess peer effects among researchers SOCIAL SCIENCE RESEARCH Rawlings, C. M., McFarland, D. A. 2011; 40 (3): 1001-1017

  View details for DOI 10.1016/j.ssresearch.2010.10.002

  View details for Web of Science ID 000289497100021

• The Ties that Influence: How Social Networks Channel Faculty Grant Productivity. Social Science Research Rawlings, C., McFarland, D. A. 2011; 40: 1001-1017
• Network Search: A New Way of Seeing the Education Knowledge Domain TEACHERS COLLEGE RECORD Mcfarland, D., Klopfer, E. 2010; 112 (10): 2664-2702

  View details for Web of Science ID 000284327900008

• Toward a Historical Sociology of Social Situations AMERICAN JOURNAL OF SOCIOLOGY Diehl, D., Mcfarland, D. 2010; 115 (6): 1713-1752

  View details for Web of Science ID 000278374600002

• Organization by Design: Supply- and Demand-side Models of Mathematics Course Taking SOCIOLOGY OF EDUCATION McFarland, D. A., Rodan, S. 2009; 82 (4): 315-343

  View details for Web of Science ID 000272224000002

• Inside Student Government: The Variable Quality of High School Student Councils TEACHERS COLLEGE RECORD McFarland, D. A., Starmanns, C. 2009; 111 (1): 27-54

  View details for Web of Science ID 000269711000002

• Curricular flows: Trajectories, turning points, and assignment criteria in high school math careers SOCIOLOGY OF EDUCATION McFarland, D. A. 2006; 79 (3): 177-205

  View details for Web of Science ID 000240413400001

• Bowling young: How youth voluntary associations influence adult political participation AMERICAN SOCIOLOGICAL REVIEW McFarland, D. A., Thomas, R. J. 2006; 71 (3): 401-425

  View details for Web of Science ID 000238812900003

• The Art and Science of Dynamic Network Visualization. Journal of Social Structure, Permalink: http://www.cmu.edu/joss/content/articles/volume7/deMollMcFarland/ Bender-deMoll , S., McFarland, D. A. 2006; 7 (2)
• Motives and contexts of identity change: A case for network effects 98th Annual Meeting of the American-Sociological-Association McFarland, D., Pals, H. SAGE PUBLICATIONS INC. 2005: 289–315

  View details for Web of Science ID 000236530500001

• Dynamic network visualization AMERICAN JOURNAL OF SOCIOLOGY Moody, J., McFarland, D., Bender-deMoll, S. 2005; 110 (4): 1206-1241

  View details for Web of Science ID 000229472000011

• Resistance as a social drama: A study of change-oriented encounters AMERICAN JOURNAL OF SOCIOLOGY McFarland, D. A. 2004; 109 (6): 1249-1318

  View details for Web of Science ID 000221651700001

• When tensions mount: Conceptualizing classroom situations and the conditions of student-teacher conflict Conference on Stability and Change in American Education McFarland, D. A. ELIOT WERNER PUBLIATIONS INC. 2003: 127–150

  View details for Web of Science ID 000189466700008

• Student resistance: How the formal and informal organization of classrooms facilitate everyday forms of student defiance AMERICAN JOURNAL OF SOCIOLOGY McFarland, D. A. 2001; 107 (3): 612-678

  View details for Web of Science ID 000175830600003