Modeling the Propagation of Fake News on Social Media

We are examining the network effects of political content propagation in social media to understand how the bias and truthfulness of content affect its spread.

Name of research group, project, or lab
Martonosi
Why join this research group or lab?

The propagation of fake news has directly impacted national and global elections as well as other current events such as protests for racial justice and the pandemic.  

Representative publication
Logistics Information:
Project categories
Computer Science
Engineering
Mathematics
Data Science
Operations Research
Optimization
Student ranks applicable
Sophomore
Junior
Senior
Student qualifications

The interested students should have proficiency and/or a desire to learn R, as well as proficiency in python.  It would be helpful if the students have taken courses in probability, statistics and/or operations research beyond core.

Time commitment
Fall - Part Time
Spring - Part Time
Compensation
Academic Credit
Number of openings
2
Techniques learned

We will be using techniques from probability, optimization, and data science.  The student researchers will assist with surveying the literature, developing experimental protocols, writing simulation code, analyzing results, and writing a manuscript. 

- Literature review

- Technical writing

- Data collection, cleaning, analysis

- Simulation

- Experimental design

- Probability and statistics

- Optimization

Contact Information:
Mentor name
Susan Martonosi
Mentor email
martonosi@hmc.edu
Mentor position
Professor of Mathematics
Name of project director or principal investigator
Susan Martonosi
Email address of project director or principal investigator
martonosi@g.hmc.edu
2 sp. | 4 appl.
Hours per week
Fall - Part Time (+1)
Fall - Part TimeSpring - Part Time
Project categories
Engineering (+5)
Computer ScienceEngineeringMathematicsData ScienceOperations ResearchOptimization