FACULTY OF COMMUNICATION

Department of New Media and Communication

NMC 467 | Course Introduction and Application Information

Course Name
Data: Theory and Practice
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
NMC 467
Fall/Spring
1
2
2
4

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives This course introduces the students to the basic concepts of data, and helps them develop an understanding of the societal consequences of digitalization. This course also acquaints the students with the basics of storytelling with data, using datasets and visualization tools.
Learning Outcomes The students who succeeded in this course;
  • Think critically about the implications of data in society;
  • Demonstrate literacy skills relevant to data and its politics;
  • Employ datasets in storytelling;
  • Understand how the type of data impacts the type of visualization;
  • Develop the necessary skills to deploy basic tools to analyze and visualize data.
Course Description This course is about the social transformations brought on by the proliferation of digital data in society. The course has two parts: lecture and practice. In the first part of the course, students will explore the various aspects of data in social life through lectures, and the second part will complement the first by hands-on activities, helping them develop their own project in practice.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
X
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction
2 Digitalization and social life Gregory, Karen, Tressie McMillan Cottom, and Jessie Daniels. 2017. Introduction, from Digital Sociologies. Beer, D., & Burrows, R. (2013). Popular culture, digital archives and the new social life of data. Theory, culture & society, 30(4), 47-71.
3 Defining big data boyd, danah and Kate Crawford. 2012. “Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon.” Information, Communication & Society 15(5):662–79. Kitchin, R. and McArdle, G. (2016) What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets, Big Data and Society.
4 Social media and the politics of big data Tufekci, Zeynep. 2017. Twitter and Tear Gas
5 Neutrality and algorithmic bias Lerman, “Big Data and Its Exclusions” Shorey, S. & Howard P. N. (2016). “Automation, Big Data, and Politics”, IjoC, 5032–5055
6 Surveillance and privacy Brayne, Sarah. 2017. “Big Data Surveillance: The Case of Policing.” American Sociological Review 82(5):977–1008. Wu and Zhang, “Automated Inference on Criminality using Face Images”
7 Data literacy Data Literacy, Herzog, Section III, pp. 65-112
8 Midterm
9 Storytelling with data
10 Spreadsheets
11 Databases and scraping
12 Data cleaning and filtering
13 Data visualization
14 Mapping and networks
15 Review of the semester
16 Review of the semester

 

Course Notes/Textbooks
Suggested Readings/Materials

Daniels, J., Gregory, K., Cottom, T. M. (2017). Digital sociologies. Bristol: Policy Press.ISBN: 1447329015.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
1
50
Seminar / Workshop
Oral Exams
Midterm
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
3
100
Weighting of End-of-Semester Activities on the Final Grade
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
1
16
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
2
32
Study Hours Out of Class
14
2
28
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
1
30
30
Seminar / Workshop
0
Oral Exam
0
Midterms
0
Final Exam
1
10
10
    Total
116

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To be able to critically discuss and interpret the theories, concepts and ideas that form the basis of the discipline of new media and communication.

2

To be able to critically interpret theoretical debates concerning the relations between the forms, agents, and factors that play a role in the field of new media and communication.

3

To have the fundamental knowledge and ability to use the technical equipment and software programs required by the new media production processes.

X
4

To be able to gather, scrutinize and scientifically investigate data in the processes of production and distribution.

X
5

To be able to use the acquired theoretical knowledge in practice.

6

To be able to take responsibility both individually and as a member of a group to develop solutions to problems encountered in the field of new media and communication.

7

To be informed about national, regional, and global issues and problems; to be able to generate problem-solving methods depending on the quality of evidence and research, and to acquire the ability to report the conclusions of those methods to the public.

X
8

To be able to critically discuss and draw on theories, concepts and ideas that form the basis of other disciplines complementing the field of new media and communication studies.

9

To be able to develop and use knowledge and skills towards personal and social goals in a lifelong process.

10

To be able to apply social, scientific and professional ethical values in the field of new media and communication.

11

To be able to collect datain the areas of new media and communication and communicate with colleagues in a foreign language ("European Language Portfolio Global Scale", Level B1).

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To be able to relate the knowledge accumulated throughout the human history to their field of expertise.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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