Take part in this project supervised by a current PhD student, getting a first-hand research experience in an academic setting and supercharging your CV with real-world experience.
More details about the Summer Research Projects scheme can be found on our info website.
The final product will be published on WDSS's research blog.
The final product will be to replicate and improve an analysis by Li (2017) which extends a model first proposed by Ormerod and Caicado (2017). In Li (2017), a basic evolutionary model with preferential attachment principle and random choice innovation mechanism is extended with two parameters: proportion and loyalty. Proportion is the parameter that specifies how many agents will re-enter the market and choose the products again at each period. Loyalty is the probability agents will conform to what they chose last time when they come to the re-contract point. Agents who are not loyal to their previous choices will follow the same decision mechanism as new entrants.
- Replicate previous analyses by Mengchu Li and adapt them to an anthropology context.
- Further Investigate the impact of the new parameters on the market concentration level, measured by the Herfindahl-Hirschman Index, through numerical simulation and (possibly) statistical tests.
- If time allows, either adapt them to an anthropology context (e.g. Bentley et al., 2014) or consider more innovative agent-based models
- Review both papers by Ormerod and Caicado (2017) and Li (2017)
- Review the existing Python implementations
- Run the updated analysis
- Write a short summary of the project for publication purposes on WDSS blog or for submission to a magazine such as Significance
- A passion for the project and, preferably, interdisciplinary data science in general
- Self-starting attitude with willingness to research and problem-solve independently
- Ability to work well in a team and clearly communicate your ideas
- Strong time-management and organisational skills.
- Coding expertise in Python (current or potential) sufficient for the completion of the project.
How to Apply
- Use the application button on this page to fill in the form where you should attach your CV and any other sources you think are relevant for the role (e.g. GitHub profile for a coding role)
as well as answering two further questions in which you should demonstrate your motivation and suitbility for the project.
- You may be contacted by WDSS to further discuss your fit for the role
- Results to be announced by the end of term 3 (Saturday 3 July 2021)
- You can apply for more than one project