Logic of Social Inquiry, 7.5 credits

Den samhällsvetenskapliga forskningens logik, 7.5 hp

771A11

Main field of study

Computational Social Science

Course level

Second cycle

Course type

Single subject and programme course

Examiner

Peter Hedström

Course coordinator

Peter Hedström

Director of studies or equivalent

Karl Wennberg
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Weeks Language Campus ECV
F7MCD Master´s Programme in Computational Social Science 1 (Autumn 2018) 201834-201838 English Norrköping, Norrköping C

Main field of study

Computational Social Science

Course level

Second cycle

Advancement level

A1X

Course offered for

  • Master´s Programme in Computational Social Science

Entry requirements

A bachelor's degree or equivalent in the humanities, social-, cultural-, behavioural-, natural-, computer-, or engineering-sciences.
English corresponding to the level of English in Swedish upper secondary education (English 6/B).

Intended learning outcomes

After completion of the course, the student should at an advanced level be able to:

  • describe and critically examine common modes of social inquiry used within the social sciences;
  • appraise the role of micro-level social processes in explanations of macro-level outcomes, and critique explanations of macro outcomes on this basis;
  • critically assess the strengths and weaknesses of computational social science as compared to other approaches to social research, relating computational approaches to micro- and macro-levels of analysis;
  • identify and formulate research questions that can be answered with the tools of computational social science;
  • critically analyse and integrate knowledge gained through readings and discussions, and express this knowledge in class and in writing,
  • describe the ethical principles regarding the production and presentation of original social research;
  • account for and apply the rules for the treatment of academic references and the principles of source criticism.

Course content

This course provides an advanced introduction to the logic of inquiry and research design in the social sciences. The readings cover issues ranging from the nature of scientific explanations and causal inquiry to the variety of research methodologies available to social scientists.  After introducing and critically examining the most important modes of social inquiry currently in practice, the course focuses on computational social science, its defining characteristics, and how computational approaches can improve our understanding of the complex social processes through which macro-level social outcomes are brought about, and by which they can be explained. 

Teaching and working methods

The teaching consists of lectures, readings, and seminars. Homework and independent studies are a necessary complement to the course.
Language of instruction: English.

Examination

The course is examined through written assignments, active participation in seminars, and a written individual final assignment. Detailed information about the examination can be found in the course's study guide.

Students failing an exam covering either the entire course or part of the course twice are entitled to have a new examiner appointed for the reexamination.

Students who have passed an examination may not retake it in order to improve their grades.

Grades

ECTS, EC

Other information

Planning and implementation of a course must take its starting point in the wording of the syllabus. The course evaluation included in each course must therefore take up the question how well the course agrees with the syllabus. 

The course is carried out in such a way that both men´s and women´s experience and knowledge is made visible and developed.

Department

Institutionen för ekonomisk och industriell utveckling
Code Name Scope Grading scale
ESSX Essay 7.5 credits EC

Books

Friedman, M., (1953) The methodology of positive economics, Essays in Positive Economics Chicago University Press
Hedström, Peter, (2005) Dissecting the social : on the principles of analytical sociology, Cambridge : Cambridge University Press, 2005

ISBN: 0521792290, 9780521792295, 0521796679, 9780521796675

Hedström, Peter, Bearman, Peter S., (2009) The Oxford handbook of analytical sociology Oxford ; New York : Oxford University Press, 2009.

ISBN: 0199215367, 9780199215362, 9780191550577

Hedström, Peter, Bearman, Peter S., (2009) The Oxford handbook of analytical sociology Oxford ; New York : Oxford University Press, 2009.

ISBN: 0199215367, 9780199215362, 9780191550577

666-687 Brückner, H Surveys

Hedström, Peter., Swedberg, Richard., (1998) Social mechanisms: an analytical approach to social theory Cambridge University Press

ISBN: 9780521593199, 9780521596879, 0521593190, 0521596874

Sørensen, A Theoretical mechanisms and the empirical study of social processes

Schelling, Thomas, (1978) Micromotives and Macrobehavior

ISBN: 147367347X, 9781473673472

Shadish, William R., Cook, Thomas D., Campbell, Donald T., (2002) Experimental and quasi-experimental designs for generalized causal inference Boston : Houghton Mifflin , cop. 2002

ISBN: 0395615569

Webster, Murray, Sell, Jane, (2007) Laboratory experiments in the social sciences Amsterdam ; Boston : Academic Press/Elsevier, c2007.

ISBN: 9780123694898, 0123694892

Articles

Andersson, C., The end of theory: the data deluge makes the scientific method obsolete, Wired Magazine 2008

https://archive.wired.com/science/discoveries/magazine/16-07/pb_theory

Arnout van de Rijt, Soong Moon Kang, Michael Restivo, Akshay Patil, Field experiments of success-breeds-success dynamics, PNAS 2014, 111:6934-6939
Baldassarri, Delia, Abascal, Maria, Field Experiments Across the Social Sciences Annual Review of Sociology 2017, Vol. 43, p41-73. 25p.
Bearman, P. S., Moody, J., Stovel, K., Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks, American Journal of Sociology 2004, 110(1), 44-91
Blei, D.M., Probabilistic Topic Models Surveying a suite of algorithms that offer a solution to managing large document archives, 2012

http://www.cs.columbia.edu/~blei/papers/Blei2012.pdf

Collier, D., Understanding Process Tracing, PS: Political Science & Politics 2011, 44(04): 823-830
Diane Vaughan, Theorizing disaster: Analogy, historical ethnography, and the Challenger accident Ethnography 2004 5(3): 315-347
Duncan J. Watts,, Common Sense and Sociological Explanations 1 American Journal of Sociology 2014, 120(2), 313–351
Epstein, J. M., Agent-Based Computational Models and Generative Social Science, 1999

http://vermontcomplexsystems.org/share/papershredder/epstein-complexity-1999.pdf

Ernst Fehr, Simon Gächter,, Cooperation and Punishment in Public Goods Experiments, American Economic Review 2000, 90:980-994
Espeland, W. N., Sauder, M., Rankings and Reactivity: How Public Measures Recreate Social Worlds American Journal of Sociology 2007, 113(1):1–40
Glenn Firebaugh, author, Matthew B. Schroeder, author, Does Your Neighbor’s Income Affect Your Happiness?1 American Journal of Sociology 2009, 91:1309-1335
Hedström, Peter, Ylikoski, Petri,, Causal mechanisms in the social sciences, Annual Review of Sociology 2010, 36:49-67
Jackson, M., Cox, D.R., Jackson, M., Cox, D.R., The principles of experimental design and their application in sociology, Annual Review of Sociology 2013 39:27-49
James S. Coleman,, Social Theory, Social Research, and a Theory of Action, American Journal of Sociology 1986, 91:1309-1335
Justin Grimmer, A Bayesian Hierarchical Topic Model for Political Texts: Measuring Expressed Agendas in Senate Press Releases, Political Analysis 2010, 18:1-35

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/74F30D05C220DB198F21FF5127EB7205/S1047198700012298a.pdf/bayesian_hierarchical_topic_model_for_political_texts_measuring_expressed_agendas_in_senate_press_releases.pdf

Kees Keizer, Siegwart Lindenberg, Linda Steg, The Spreading of Disorder, Science 2008, 322:1681-1685
Keuschnigg, Marc, Lovsjö, Niclas, Hedström, Peter, Analytical sociology and computational social science, Journal of Computational Social Science 2017

https://link.springer.com/content/pdf/10.1007%2Fs42001-017-0006-5.pdf

Lazer, D., Computational Social Science, Science 2009, 323 (5915), 721-723
León-Medina, F.J., Analytical Sociology and Agent-Based Modeling: Is Generative Sufficiency Sufficient? Sociological Theory 2017, 35(3):157-178

http://journals.sagepub.com/doi/pdf/10.1177/0735275117725766

Michael P. H. Stumpf, Mason A. Porter, Critical Truths About Power Laws, Science 2012, 335 (6069), 665-666
Mützel, Sophie, Facing Big Data: Making sociology relevant, Big Data & Society 2015, 2(2), 1-4
Roberts, Margaret E., Stewart, Brandon M., Airoldi, Edoardo M., A Model of Text for Experimentation in the Social Sciences, Journal of the American Statistical Association 2016

https://www.tandfonline.com/doi/full/10.1080/01621459.2016.1141684

Salganik, Matthew J., Watts, Duncan J., Web-Based Experiments for the Study of Collective Social Dynamics in Cultural Markets, Topics in Cognitive Science 2009, 1: 439-468
Watts, D.J., Computational Social Science: Exciting Progress and Future Directions, The Bridge: Linking Engineering and Society 2013, 43(4), 5–10

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