COVID-19 has transformed people’s lives in every aspect. Travel patterns and work patterns are also changed. This project aims to leverage social media data (e.g., tweets, facebook posts, Reddit posts) to mine people’s travel patterns and the timeline of telecommute using Natural Language Processing (NLP). Research questions are:

  1. What’s the timeline of people going back to work?
  2. What travel modes would people select after going back? Would it be different or the same as those pre-pandemic?
  3. How would these patterns influence NYC’s traffic congestion pattern?
  4. Can we use social media data to infer NYC traffic congestion?

Skill requirements are:

  1. using a suitable coding tool (such as Python) to extract data from social media;
  2. using a visualization tool (such as Python, MATLAB, or Processing) to analyze data and plot patterns;
  3. generating figures, graphs, tables, or statistical models to present results.
  4. Analyze the association between social media data and real-world traffic patterns

This is an UNPAID research project.

Faculty Advisor

Project Timeline

  • Earliest starting date: 9/6/21
  • End date: 12/31/21
  • Number of hours per week of research expected during Fall 2021: ~20

Candidate requirements

  • Skill sets:
    1. using a suitable coding tool (such as Python) to extract data from social media;
    2. using a visualization tool (such as Python, MATLAB, or Processing) to analyze data and plot patterns;
    3. generating figures, graphs, tables, or statistical models to present results.
    4. Analyze the association between social media data and real-world traffic patterns
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes