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.

  • Estimation of Multipolar Polarization: I have developed a measure to estimate how polarized the political discourse is on Facebook and Twitter. However, the measure can only be calculated for two opposing opinions. How can we deal with scenarios where users have multiple opinions, such as supporting multiple different political parties? This project can benefit from NLP techniques to generate word embeddings (GPT, W2V, …) and a machine learning side (PCA, NNMF, t-SNE, …) so not only for network enthusiasts!
  • Network Analysis of Sports: we can build networks of who-beats-who in sports and use them to build better ranking systems, making a sport comparison of what are the most predictable sports, test some hypothesis of cumulative advantage by comparing European leagues with American ones using the draft system, and more.
  • Segregation of Genres: using data from users rating things (books, videogames, songs, movies, …) we can use techniques to determine how isolated communities of genres are. Are people liking sci-fi books completely ignoring those liking fantasy? Or romance?
  • Network Generating Model: I have an algorithm that, given a network, it outputs the connection rules underlying it, by exploring frequent patterns. If we are given a set of rules, can we generate a new network from scratch that looks like the one we obtained the rules from?
  • Build Multilayer Networks from Graphic Novels: making a network out of a work of fiction is helpful to study literary theory and gender norms in fiction. Most works so far build networks with a single type of interaction, but multilayer and signed network could potentially be more useful.
  • 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?
  • Network Analysis Library for Julia: Julia is a nice and fast programming language, more suitable than Python to data science. There are some small network analysis libraries, but nothing comes close to the completeness of Networkx. You can help me making a new complete network analysis Julia package by implementing and testing a handful of network analysis functions.
  • Some other random keywords (ask me about it!): economic complexity of the Roman Empire, network entropy, node vector clustering, phoneme networks, utilitarian “would you rather?” game, US health insurance data, …