Project Ideas

Below are some ideas for Master’s theses, bachelor projects and other projects for students at the IT University of Copenhagen. Contact me (mcos@itu.dk) to get started.

  • Human mobility and development: Using a new dataset estimating the development level of places in developing countries, we can estimate the link between wealth and the place where one lives. Then we can investigate the effect of lockdowns on the livelihood of people: if human mobility gets much harder, are all people equally affected or is there a disproportionate negative impact for people living in low-income communities?
  • How polarized is a social network?: Current measures of polarization only look at the opinions of users in isolation, but we need to look at the network structure to truly be able to tell whether a system is polarized or not. In this project you would use measures of network distance and co-variance to discover how divisive Facebook and Twitter networks truly are.
  • Study propagation on complex networks: How fast does a disease infect a social network? Is there a correlation between how two different diseases infect your friends? Can we tell how segregate messages are among communities ? Can we use these questions to figure out whether a message in a viral marketing campaign is passing through social connections that we are not able to observe? Can we answer these questions on networks that are evolving over time?
  • Multilayer Graph Association Rule Mining: Apply a newly developed multilayer graph mining algorithm to study the evolution of multilayer networks and perform multilayer link prediction: detect which new edges are likely to appear in the network, and in which layers. For instance: are Linkedin connections precursors of Facebook friendship? Is being connected on Twitter helping to create a social community in another platform? Is it better to take classes together at ITU or to be part of a study group, if we want to be friends?
  • Flagging fake news on social media: I wrote a paper with Luca Rossi showing that, on social media, the most neutral and factual posts attract most flags from two polarized sides (left vs right). In this project, we can challenge some assumptions of that work. For instance: what if one of the two sides is less tolerant than the other?
  • Some other random keywords. If you find any of these intriguing, you can talk to me about them to see if we can carve a project out of them: Hot-or-not utilitarianism solver; Network similarity measures; Rise of the “shaming” subreddits; Multiplex Economic Complexity Index; Inflation of News; Central place theory and synthetic networks; The Oscar effect; Content-creation networks and meritocracy; Random geometric networks …