Information Package / Course Catalogue
Ai Usage in New Media
Course Code: YMİ204
Course Type: Required
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 1
Prt.: 2
Credit: 2
Lab: 0
ECTS: 6
Objectives of the Course

The aim of this course is to examine the theoretical and practical applications of artificial intelligence (AI) technologies in the fields of new media and communication. The course will cover the impact of AI on digital content production, social media management, algorithmic recommendation systems, data analysis, news production, visual and video content design, audience analysis, advertising, digital marketing, personalized communication, and media ethics. Students are expected to become familiar with AI-powered new media tools, evaluate their impact on communication processes, critically analyze AI-generated content, and develop AI-based content and communication strategies in the new media field while considering ethical responsibilities.

Course Content

The concept of artificial intelligence, machine learning, algorithms, big data, the relationship between new media and AI, social media algorithms, content recommendation systems, AI-assisted text generation, visual and video production tools, news writing and automated journalism, the use of AI in digital advertising, target audience analysis, personalized communication, chatbots , virtual assistants, disinformation, deepfake technologies, algorithmic bias, digital privacy, copyright, AI ethics, and AI-assisted project development in the field of new media.

Name of Lecturer(s)
Learning Outcomes
1.It explains the concept of artificial intelligence, its basic components, and its uses in the field of new media.
2.Algorithms used in new media environments evaluate big data, machine learning, and automation systems in terms of communication processes.
3.AI-powered software analyzes the production processes of text, image, video, audio, and social media content.
4.This study evaluates the impact of artificial intelligence on digital journalism, advertising, public relations, social media management, and audience analysis.
5.It creates AI-powered new media content or campaign designs while considering ethical principles, copyright, privacy issues, and algorithmic bias.
Recommended or Required Reading
1.Russell, S. ve Norvig, P. Artificial Intelligence: A Modern Approach. Pearson, 2021
2.Kaplan, A. ve Haenlein, M. “Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence.” Business Horizons, 2019.
3.Couldry, N. ve Hepp, A. The Mediated Construction of Reality. Polity Press, 2017.
4.McQuail, D. McQuail’s Mass Communication Theory. Sage Publications, 2010.
5.Floridi, L. The Ethics of Artificial Intelligence. Oxford University Press, 2023.
6.Broussard, M. Artificial Unintelligence: How Computers Misunderstand the World. MIT Press, 2018.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Artificial Intelligence: Basic Concepts, Historical Development, and its Relationship with New Media.
Week 1 - Preparation Work
Week 2 - Theoretical
Algorithms, Big Data, and Machine Learning in the New Media Ecosystem
Week 2 - Preparation Work
Week 3 - Theoretical
The Use of Artificial Intelligence on Social Media Platforms and Content Recommendation Systems
Week 4 - Theoretical
AI-Powered Text Generation: News, Blog, Advertising, and Social Media Content
Week 5 - Theoretical
Artificial Intelligence Tools in Visual, Video, and Audio Production
Week 6 - Theoretical
The Use of Artificial Intelligence in Digital Marketing, Advertising, and Audience Analysis
Week 7 - Preparation Work
Chatbots, Virtual Assistants, and Automated Customer Communication
Week 8 - Theoretical
Overall evaluation of the course.
Week 8 - Preparation Work
Week 9 - Theoretical
Artificial Intelligence and Journalism: Automated News Generation, Data Journalism, and Editorial Processes
Week 10 - Theoretical
Disinformation, Deepfakes, and AI-Powered Media Manipulation
Week 11 - Theoretical
AI Ethics: Algorithmic Bias, Transparency, Privacy, and Copyright
Week 12 - Theoretical
AI-Powered Content and Campaign Design
Week 13 - Theoretical
AI-Powered Content and Campaign Design
Week 14 - Theoretical
Student Project Presentations and AI-Based Content Assessments
Week 15 - Theoretical
Overall evaluation of the course.
Week 15 - Preparation Work
Week 16 - Preparation Work
Week 17 - Preparation Work
Week 18 - Preparation Work
Week 19 - Preparation Work
Week 20 - Preparation Work
Week 21 - Preparation Work
Week 22 - Preparation Work
Week 23 - Preparation Work
Week 24 - Preparation Work
Week 25 - Preparation Work
Week 26 - Preparation Work
Week 27 - Preparation Work
Week 28 - Preparation Work
Week 29 - Preparation Work
Week 30 - Preparation Work
Week 31 - Preparation Work
Week 32 - Preparation Work
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%10
Project1%10
Midterm Examination1%20
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory141242
Lecture - Practice141128
Assignment115116
Project120121
Midterm Examination116117
Final Examination120121
TOTAL WORKLOAD (hours)145
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
PÇ-15
PÇ-16
OÇ-1
4
4
4
5
OÇ-2
5
4
4
5
OÇ-3
4
5
5
5
OÇ-4
4
5
4
5
OÇ-5
4
5
4
5
4
5
Adnan Menderes University - Information Package / Course Catalogue
2026