Identify discussions on a topic

People discuss on platforms like X (Twitter), LinkedIn, Reddit, DevRant, Glassdoor, etc. These discussions are valuable sources of information on the concurrent problems and their prospective solutions.

This project focuses on identifying fairness issues experienced by software developers at work. Each bachelor thesis will pick a platform to identify fairness issues software developers discuss and their prospective solutions, if any.

At the end of this project, the student is expected to develop programming skills and a working knowledge of natural language processing, information retrieval, and application of large language models such as ChatGPT.

Available spots: 5

Literature

Aiello, L. M., Petkos, G., Martin, C., Corney, D., Papadopoulos, S., Skraba, R., … & Jaimes, A. (2013). Sensing trending topics in Twitter. IEEE Transactions on multimedia, 15(6), 1268-1282.

Yuan, Q., Cong, G., Ma, Z., Sun, A., & Thalmann, N. M. (2013, August). Who, where, when and what: discover spatio-temporal topics for twitter users. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 605-613).

Paul, M. J., & Dredze, M. (2012). A model for mining public health topics from Twitter. Health, 11(16-16), 1.

Nugroho, R., Paris, C., Nepal, S., Yang, J., & Zhao, W. (2020). A survey of recent methods on deriving topics from Twitter: algorithm to evaluation. Knowledge and information systems, 62(7), 2485-2519.