Mid-Term Project

Xoxoday.com: Customer Engagement Through Social Media

Published

December 10, 2025

Project Overview

The mid-term project is a group assignment that requires you to apply network analysis methodologies to solve a real business problem. You will work with the case study “Xoxoday.com: Customer Engagement Through Social Media” to demonstrate your understanding of network concepts and analytical techniques.

ImportantKey Information
  • Group Size: 3-4 students per group
  • Due Date: November 10, 2025
  • Presentation: November 12, 2025
  • Weight: 50% of final grade

Deliverables

  1. Written Report (3,000 words maximum)
  • Executive summary
  • Methodology
  • Results & analysis
  • Your recommendations to address the case problem
  1. Reproducible Code
  • Well-documented computer code1
  • Clear data preprocessing steps
  • Commented analysis procedures
  • Code that generates all figures and tables in the report

Case Materials

Submission (November 10, 15:59 PM)

Upload a single compressed folder (.zip or .tar.gz) containing:

  1. Report (PDF format, max 3,000 words)
  2. Computer code with processed datasets
  3. README.md with instructions to reproduce results

Presentation Preparation (November 12)

  • Bring presentation on USB drive or have it accessible online
  • Prepare for 10-minute presentation + 5-minute Q&A
  • All team members must participate in the presentation
  • Be ready to answer technical and business questions
  • Presentation schedule available in due course

Getting Help

Office Hours

  • When: Wednesdays 15:00 - 17:00, or by appointment
  • Where: Faculty office or online (schedule via email)
  • Purpose: Methodology guidance, technical support, feedback on progress

Resources

  • Course materials: Slides, readings, and case discussions
  • Peer collaboration: Discuss concepts (but not share solutions) with other teams

Academic Integrity

WarningImportant Reminders
  • Collaboration within teams is expected and encouraged
  • Collaboration between teams should be limited to conceptual discussions
  • All sources must be properly cited using academic citation standards
  • Code originality: While you may reference online resources, the analysis must be your own work
  • Data integrity: Do not modify the provided dataset beyond standard preprocessing

Success Tips

TipRecommendations for Success
  1. Start early: Network analysis can be computationally intensive
  2. Plan your approach: Discuss methodology before diving into coding
  3. Iterate frequently: Regular team check-ins and progress reviews
  4. Focus on business value: Always connect technical findings to business implications
  5. Document everything: Keep detailed notes of your analytical choices and assumptions
  6. Practice your presentation: Rehearse timing and smooth transitions between speakers

Good luck with your mid-term project! This is an excellent opportunity to apply network analysis to real-world challenges and develop skills highly valued in today’s data-driven business environment.

Footnotes

  1. Admitted programming languages are C, C++, Julia, Python, R, Rust.↩︎

  2. Data in Excel format. You can red that using R’s readxl or Pandas’s read_excel↩︎