Data Science and Social Analysis Cross-disciplinary Specialty

With the development of science and technology and the changes in social needs, the boundaries between the old tradition and the contemporary society are more and more blurred; problems faced by contemporary society often need to be solved through new thinking, new methods, and new tools. The “data science”, which collects, organizes, analyzes, and interprets data, is a new cross-domain knowledge that has recently received much attention and has potential for future development. In short, data science is the transformation of data into knowledge that can be used for decision-making and action. With the availability of a wide range of materials, it is significant and valuable to use this information and turn it into a decision-making basis for individuals, businesses, and governments.

Data scientists need to be able to ask questions, gather relevant information, do the correct analysis, and translate the results so that they can be understood for decision making. Therefore, traditionally, data scientists need to have three capabilities: domain knowledge, mathematical analysis capabilities, and computer information capabilities. The different focuses on these three capabilities are the development of data science talents with different characteristics. The data scientists of the new era need to be able to explore and mine primary sources, in addition to organizing and analyzing the data accordingly. The design of the cross-domain expertise of the "Information Science and Social Analysis" is hoped to give full play to the traditional training and advantages of the College of Social Sciences in "domain knowledge" and "social analysis", and to further integrate the computer information capabilities required in the new era, educate students to have data analysis talents for the future scientific application of data.

In general, this cross-domain expertise is designed to develop cross-domain talent with the knowledge, data, and quantitative analysis in the social sciences. The course design is based on the professional courses of each department of the school. It trains students' analysis and insight on contemporary economic, political and social issues. Combined with the core courses of the school and inter-departmental data science, the course is designed to build students' applications of computers and programs. Through the training of this course, students will have the ability to observe problems, collect data, analyze data, and interpret the results of the analysis. As a result of the increasing number of digital data and calculus tools, they will be able to grasp opportunities and respond to society.
Data Science and Social Analysis Cross-disciplinary Specialty is terminated, and replaced by "Bachelor Degree of College of Social Science". Please refer to the announcement for detail information.

Teaching Units

Host: Department of Economics, College of Social Sciences. Participants from other Teaching Units: Department of Politics, Department of Economics, Department of Social Sciences, Graduate Institute of National Development, Graduate Institute of Journalism, Department of Computer Science and Information Engineering, Department of Information Management, College of Science, College of Electrical Engineering and Computer Science, College of Management, Center of General Education

Courses and Degree

The curriculum of this cross-disciplinary specialty consists of three levels.

(1) Level 1 – Fundamental Common Courses:

1. General education courses – Chinese Literature, Foreign Languages, Physical Education, and Service Learning. 
2. Liberal Education courses – Language Writing, Communication Coordination, Media and Information Literacy, Design Thinking, Aesthetics, and Ethics, etc.
3. Students of the College of Social Sciences should take the first-year required courses according to their majors.  
4. Data Science and Social Inquiry (ECON5154) – a required course for this cross-domain specialty. This course introduces the latest development and applications of data science in all areas of social sciences.

(2)Level 2 – Major-Specific Core Courses: (9 credits)

1. Economics: Microeconomics, Macroeconomics, and other required courses from the sophomore year and above.
2. Sociology: Social Psychology, Social Research Methods, and other required courses from the sophomore year and above.
3. Political Science: Comparative Government, Applied Statistics, and other required courses from the sophomore year and above.
4. Social Work: Social Casework, Social Work Research Methods, and other required courses from the sophomore year and above.
   This category of the courses does not include the first-year required courses from the College of Social Sciences.  

(3)Level 3 – Cross-disciplinary Specialty Courses: (18 credits)

1. Computer-related courses (6 credits): data structure and algorithm (Data), programming (Program), data engineering (Engineering), programming for Business Computing (Business Program). The students must take credits from at least 2 out of the 4 groups.
2. Cross-disciplinary Application-oriented Courses (9 credits): courses related to the application and quantitative analysis of information technology in the College of Social Sciences. 
   Special attention: students should take computer-related courses for at least 6 credits from at least two out of the three modules: Data, Program, and Business Program. It is also important to note that 6 out of the 9 credits for the cross-disciplinary courses must be taken beyond the student’s original department or have been classified as cross-disciplinary.  
3. Capstone Course (3 credits): Give students the opportunity to apply what they have learned in real internship jobs and contests. 
   Please see the link below for the detailed list of the cross-disciplinary courses. (in Chinese)
   Data Science and Social Analysis Cross-disciplinary Specialty Courses

Important Deadlines

Students who have met the qualifications of the cross-disciplinary specialty may submit the application for the degree to the Department of Economics during the period of their studies. The application for the first semester should be submitted before the end of October. The application for the second semester should be submitted before the end of March. After completing the three-level courses according to the curriculum, the student’s school documents such as the degree certificate, and the year report will be marked with the “Data Science and Social Analysis" profession.