| Course Type | Elective Course |
|---|
| Course Level | Master's Degree With Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 9 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- Learn the methods and techniques of big data analytics.
- Learn the skills to apply big data analytics methods and techniques on psychological data.
- Evaluate ethical and privacy issues in analyzing psychological data.
- Conduct independent research using big data analysis tools for psychological research.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | This course aims to examine the use of big data analytics methods in various areas of social psychology. It will teach how big data sources can be analyzed to understand the behavior of individuals, groups and societies in the context of social psychology. The course aims to teach students the theoretical foundations of big data analytics with practical applications on social media data, psychological test results, observations and other types of social psychological data. It also aims to develop students' analytical thinking, problem solving and research skills by using big data analytics in research and applications in the field of social psychology. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Introduction and Basic Concepts |
|
2nd Week |
Characteristics and Sources of Social Psychological Data |
|
3rd Week |
Basic Statistical Methods and Psychological Data Analysis |
|
4th Week |
Data Cleaning and Preprocessing |
|
5th Week |
Data Visualization and Presentation of Social Psychological Data |
|
6th Week |
Machine Learning Fundamentals |
|
7th Week |
Deep Learning and Social Psychological Applications |
|
8th Week |
Data Analytics on Social Interactions and Group Dynamics |
|
9th Week |
Analyzing Social Media and Online Behavior |
|
10th Week |
Modeling Psycho-social Behavior |
|
11th Week |
Using Big Data in Social Psychology Research |
|
12th Week |
Big Data Analytics in Social Psychological Testing |
|
13th Week |
Ethical and Privacy Issues |
|
14th Week |
Final Presentations |
|
15th Week |
General Evaluation |
|
| Recommended or Required Reading | Woo, S. E. E., Tay, L. E., & Proctor, R. W. (2020). Big data in psychological research. American Psychological Association.
Bahga, A., & Madisetti, V. (2016). Big data science & analytics: A hands-on approach. |
|---|
| Planned Learning Activities and Teaching Methods |
- Discussion
- Lecture
- Questions/Answers
- Other
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Project |
1 |
60 |
| Total(%) |
|
60 |
| Contribution of In-term Studies to Overall Grade(%) |
|
60 |
| Contribution of Final Examination to Overall Grade(%) |
|
40 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
|
|
|
| Preparation for Quiz |
|
|
|
| Individual or group work |
15 |
10 |
150 |
| Preparation for Final exam |
1 |
25 |
25 |
| Course hours |
15 |
3 |
45 |
| Preparation for Midterm exam |
|
|
|
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
3 |
3 |
| Homework |
|
|
|
| Project |
1 |
50 |
50 |
| Total Work Load | 273 |
| Total Work Load / 30 (h) | 9.1 |
| ECTS Credit of the Course | 9 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
