2020 Faculty Courses School of Environment and Society Department of Social and Human Sciences Graduate major in Social and Human Sciences
Graduate Lecture in Cognition, Mathematics and Information S1B
- Academic unit or major
- Graduate major in Social and Human Sciences
- Instructor(s)
- Kazuhiro Kezuka
- Class Format
- Lecture (Zoom)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 1-2 Wed (W9-707)
- Class
- -
- Course Code
- SHS.M442
- Number of credits
- 100
- Course offered
- 2020
- Offered quarter
- 2Q
- Syllabus updated
- Jul 10, 2025
- Language
- Japanese
Syllabus
Course overview and goals
In recent years, computational social science has been emerging. Computational social science is an area that collects traces of people's behavior on the Internet ("digital footprint") and analyzes them. In this course, students will learn how to analyze the social survey and the vast amount of data in the digital era.
Course description and aims
By the end of this course, students will be able to:
1) understand and practice the social survey methodology in the digital age.
2) analyze data which you collected.
Keywords
social survey, big data, statistical analysis
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Students summarize the textbook on paper and report it. Students discuss based on the paper. At the last class, students must plan a social survey and make a presentation of it.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Guidance | Understand what computational social science is. |
| Class 2 | Observing behavior | Understand big data and strategy of analyzing them. |
| Class 3 | Asking questions | Understand social surveys in digital era. |
| Class 4 | Running experiments | Understand experiments of social sciences in digital era. |
| Class 5 | Creating mass collaboration | Understand the strategies to develop our research with collaboration. |
| Class 6 | Ethics | Understand the ethics of social surveys in digital era. |
| Class 7 | Presentation of survey plan | Make a persuasive presentation of survey plan. |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
Salganik, M. J., 2017, Bit by Bit: Social Research in the Digital Age, Princeton University Press. (Japanese translated edition will be published in April 2019)
Reference books, course materials, etc.
None required.
Evaluation methods and criteria
summary resume: 30%, final presentation: 30%, commitment: 40%
Related courses
- SHS.M443 ： Graduate Lecture in Cognition, Mathematics and Information F1A
- SHS.M444 ： Graduate Lecture in Cognition, Mathematics and Information F1B
- SHS.M461 ： Graduate Methodologies in Cognition, Mathematics and Information S1
Prerequisites
None required.
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
kkezuka[at]ila.titech.ac.jp