CS4003 · BS elective · 4 credits

Privacy & Security in Online Social Media

The threat models, defences and design choices behind privacy on today's social platforms.

Instructor Prof. Ponnurangam Kumaraguru Term As offered Prereq none

§ 1Calendar

  • Quiz 1—
  • Quiz 2—
  • End-term examination—

§ 2Previous Year Questions

No papers uploaded yet.

§ 3Resources

Course material2

Notes2

CS4003 · BS elective · 4 credits

Syllabus

The official course syllabus, transcribed from the IITM BS Data Science & Applications course booklet.

§ 1Course Description

This course introduces the practical aspects of large-scale analytics (big data), beginning with foundational concepts in big data and cloud computing across hardware, systems, and software, and progressing to algorithm design and execution at scale.

Lectures-Tutorials-Practicals-Credits: 4-0-0-4

§ 2Faculty

  • Prof. Ponnurangam Kumaraguru, Department of Computer Science, IIIT Hyderabad

§ 3Week-by-week

Week 1: Course overview; Social network analysis; Social media impact; Network metrics; Research projects.

Week 2: Data collection; Twitter API; Historical and live tweets; Reddit data.

Week 3: Social media text; Text processing; NLP libraries; Feature extraction.

Week 4: Fake news basics; Types; Concepts; Detection methods.

Week 5: Fake news research; Content-based detection; Misinformation datasets; Mitigation strategies.

Week 6: Social media policing; Privacy and security; Identity resolution.

Week 7: Social media nudges; Cybercrime; Hate speech detection.

Week 8: Privacy in social media; Information disclosure; Personally identifiable information (PII).

Week 9: Privacy research; Privacy laws; Anonymization.

Week 10: Ethics in social media research; Ethical challenges and solutions; Bias in social media research.

Week 11: Research paper discussions; Network centrality measures (degree, closeness, betweenness).

Week 12: Paper discussions; Course summary.