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Social Media, Ethics, and Automation
Authors and Acknowledgements
Perspectives and Biases
Book
1. Introduction
1.1. The case of Justine Sacco’s racist joke tweet
1.2. Kumail Nanjiani’s Reflections on Ethics in Tech
1.3. Learning Goals
1.4. Bibliography
2. Definitions
2.1. Social Media
2.1.1. What is Social Media?
2.1.2. Social Media Platform Examples
2.1.3. Social Media and “Real Life”
2.2. Ethics
2.2.1. What is Ethics?
2.2.2. The “Golden Rule”
2.2.3. Ethics Frameworks
2.2.4. Practice Using Frameworks
2.2.5. Ethics Frameworks Self-Assessment
2.3. Automation
2.3.1. Language Translation (Analogy)
2.3.2. Human Computers
2.3.3. Computers Speak Binary
2.3.4. First Programmers
2.3.5. Compilers and Programimng Languages
2.3.6. A program that makes one reddit post
2.3.7. Understanding the Reddit Bot Code
2.3.8. Demo: Try Running the Reddit Bot!
2.3.9. Reflections on the Bot
2.3.10. Automation in Social Media
2.4. Tying It Together
2.5. Bibliography
3. Bots
3.1. Definition of a bot
3.2. Examples of Bots (or apps)
3.3. Anatomy of a Bot
3.3.1. Organizing a Computer Program
3.3.2. Demo: Statements, Variables, and Sleep
3.3.3. Practice: Statements and Variables
3.4. Bots and Responsibility
3.5. Activity: Find Lists of Bots
3.6. Bibliography
4. Data
4.1. Anatomy of a Social Media Post
4.1.1. Data in a Social Media Post
4.1.2. Basic Data Types
4.1.3. Grouping data
4.1.4. Additional Data Types
4.1.5. Data Constraints
4.1.6. Reflection Questions
4.2. All data is a simplification of reality
4.3. Who does data fit?
4.4. How Data Informs Ethics
4.5. Data in Python and Reddit
4.5.1. Demo: Python Basic Data Types
4.5.2. Practice: Python Basic Data Types
4.5.3. Demo: Data from a Reddit Post
4.6. Design Activity: Data and Social media
4.7. Reflection: Ethics of Choosing Data Representation
4.8. Bibliography
5. History of Social Media
5.1. Pre-Internet Social Media
5.2. Web 1.0 Social Media
5.3. Web 2.0 Social Media
5.4. Looping with Lists and Dictionaries in Social Media
5.4.1. Demo: Lists and Loops
5.4.2. Demo: Dictionaries
5.4.3. Practice: Looping through lists and dictionaries
5.5. Antisocial Media
5.6. Social Media Design
5.7. Design Analysis: Use Cases and Social Media Designs
5.8. Bibliography
6. Authenticity
6.1. Authenticity
6.2. Posting Sources
6.2.1. Example: Trump Tweet Sources
6.2.2. Demo & Practice: Author Info
6.3. Inauthenticity
6.4. Personas, Code Switching, Context Collapse
6.5. Parasocial Relationships
6.6. Authenticity and Anonymity
6.7. Example: Corporate Brand Authenticity
6.8. Design Analysis: Facebook Names Rules
6.9. Bibliography
7. Trolling
7.1. What is trolling
7.2. Origins of trolling
7.3. Activity: Evaluating Trolling Examples
7.4. Responding to trolls?
7.5. Trolling a Reply Bot
7.5.1. Demo: Conditionals and String Manipulation
7.5.2. Practice: Conditionals and String Manipulation
7.5.3. Demo: Trolling a Reply Bot
7.6. Ethics and Trolling
7.7. Bibliography
8. Data Mining
8.1. Sources of Social Media Data
8.2. Data From the Reddit API
8.3. Mining Social Media Data
8.4. How is this data used
8.5. Activity: What platforms think of you
8.6. Sentiment Analysis on Social Media
8.6.1. Demo: Sentiment Analysis and Loop Variables
8.6.2. Practice: Sentiment Analysis and Loop Variables
8.6.3. Demo: Sentiment Analysis on Reddit
8.7. Data Poisoning
8.8. Reflections on Data Mining
8.9. Bibliography
9. Privacy and Security
9.1. Privacy
9.2. Security
9.3. Additional Privacy Violations
9.4. Tracking Use
9.4.1. Demo: Writing Functions
9.4.2. Practice: Functions
9.4.3. Demo: Track Use of Sentiment Analysis Code
9.5. Design Analysis: GDPR
9.6. Reflection Questions
9.7. Bibliography
10. Accessibility and Inclusivity
10.1. Disability
10.2. Accessible Design
10.3. Why It Matters Who Designs
10.4. Alt-text on Social Media
10.4.1. Alt-text
10.4.2. Demo: Alt-text From Reddit
10.5. Design Analysis: Accessibility
10.6. Bibliography
11. Recommendation Algorithms
11.1. What Recommendation Algorithms Do
11.2. Ethical Analysis of Recommendation Algorithms
11.3. Individual Concerns with Recommendation Algorithms
11.4. Societal Concerns with Recommendation Algorithms
11.5. Recommendation Bot
11.5.1. Demo: Dictionary Counters
11.5.2. Practice: Dictionary Counters
11.5.3. Demo: Recommend a Subreddit
11.6. Design Activity
11.7. Bibliography
12. Virality
12.1. Evolution and Memes
12.2. Pre-internet Virality Examples
12.3. Evolution in social media
12.4. Virality and Intention
12.5. Ethics of copying
12.6. The Experience of Going Viral
12.7. Activity: Value statements in what goes viral
12.8. Reflections
12.9. Bibliography
13. Mental Health
13.1. Social Media Influence on Mental Health
13.2. Unhealthy Activities on Social Media
13.3. Healthy Activities on Social Media
13.4. Mental Health Detection
13.5. Demo: Only positive news
13.6. Design Analysis: Mental Health
13.7. Reflection questions on mental health
13.8. Bibliography
14. Content Moderation
14.1. What Content Gets Moderated
14.2. Moderation Tools
14.3. Comparing Different Platforms
14.5. Moderation and Ethics
14.6. Activity and Reflections on Moderation
14.7. Viewing Comments and Replies
14.7.1. Tree Structures
14.7.2. Demo: Navigating Trees (recursion)
14.7.3. Demo: Display Real Reddit Comments and Replies
14.7.4. Demo: Hide Some Comments
14.8. Bibliography
15. Content Moderators
15.1. Types of Content Moderator Set-Ups
15.2. Example Moderator Set-ups
15.3. The Toll on Moderators
15.4. Game: Try being a content moderator
15.5. Bibliography
16. Crowdsourcing
16.1. Crowdsourcing Definition
16.2. Planned Crowdsourcing Examples
16.3. Ad-hoc Crowdsourcing Examples
16.4. Power Users and Lurkers
16.5. Visualizing Networks
16.6. Reflection Questions
16.7. Bibliography
17. Harassment
17.1. Individual harassment
17.2. Crowd Harassment
17.3. Who gets harassed?
17.4. Ethics and Harassment
17.5. Justifying Harassment
17.6. Stopping Harassment?
17.7. Design Example: Quoting Posts
17.8. Design Activity on Harassment
17.9. Bibliography
18. Public Criticism and Public Shaming
18.1. Shame vs. Guilt in childhood development
18.2. Online Criticism and Shaming
18.3. Perspectives on the Ethics of Public Shaming
18.4. Repair and Reconciliation
18.5. Design a Retract Feature
18.6. Bibliography
19. Capitalism
19.1. What is Capitalism?
19.2. Meta’s Capitalist Strategy
19.3. Responses to Meta’s Business Strategies
19.4. Meta vs. Users
19.5. Game: Try running a social media company
19.6. Imagining Alternatives
19.7. Programming, Gender, Status, and Money
19.8. Bibliography
20. Colonialism
20.1. What is Colonialism?
20.2. Colonialism in Tech
20.3. Colonialism in Programming
20.4. Mark Zuckerberg’s “Benevolent” Goals
20.5. Colonialism and Meta’s Strategy
20.6. Imagining Alternatives
20.7. Bibliography
21. Conclusions
21.1. What We Covered
21.2. Ethics in Tech
21.3. Going Forward
21.3.1. As a Social Media User
21.3.2. As a Member of Society
21.3.3. As a Potential Tech Worker
21.4. Final Reflection Questions
21.5. More Resources
21.6. Bibliography
Appendix
22. Making a Bot Account (Reddit)
23. Practice Solutions
23.1. Ch 3 Practice: Statements and Variables
23.2. Ch 4 Practice: Python Basic Data Types
23.3. Ch 5 Practice: Looping through lists and dictionaries
23.4. Ch 7 Practice: Conditionals and String Manipulation
23.5. Ch 8 Practice: Sentiment Analysis and Loop Variables
23.6. Ch 9 Practice: Functions
23.7. Ch 12 Solution: Dictionary Counters
24. Teaching With This Book
24.1. Pedagogical Goals and Design
24.2. Tech Set-Up
24.3. Assignments
24.3.1. Reading assignments
24.3.2. Programming practice
24.3.3. Programming Assignments
A1: Make 7 Reddit Posts
A2: Try another site
A3: Trolling a Reply Bot
A4: Political Bias
A5: Best Comments
24.3.4. Group Final Project
Project Description
Project Proposal
Project Write-Up
Project Presentation
Peer Evaluation
Your Favorite Projects
24.3.5. Writing Project
Writing Project Description
Proposal
Sourcing Topic/Scenario
Ethics Frameworks Background
Outline of Using Frameworks
Writing Project Draft
Final Project
24.4. Course Schedule
Repository
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