Narrative Economics: from Text Mining to Search for Meaning 2400-ENSM101A
The objective of this seminar is to assist students in developing the essential skills required for crafting their master's thesis. It focuses on the significance of machine learning methods, especially text mining in tackling economic phenomena. Participants will enhance their comprehension of text data analytics, especially on the topic of narrative economics. By integrating quantitative methods with innovative research concepts, the ultimate aim is to create theses that not only contribute to economic literature but also promote the application of machine learning techniques beyond their conventional scope.
During the seminar, students will develop research questions, perform comprehensive literature reviews, and perform statistical analysis of chosen phenomena. The seminar will involve individualized and regular research consultations. Python and R are the preferred programming language for the course but other choices of programming language are also accepted by the lecturer.
Potential thesis inspirations:
• Text mining analysis of contemporary economic phenomena.
• Online data source for examining economic behaviours of individuals, groups and societies.
• Narrative and storytelling as a medium of communication and sense-making of economic phenomena
The seminar aims to produce an academic paper that makes a meaningful contribution to the field of economics, demonstrating the students' ability at machine learning techniques.
Type of course
Prerequisites (description)
Course coordinators
Learning outcomes
This subject should provide a methodological basis for writing a master's thesis. After graduation, the student:
KNOWLEDGE
• Knows the connections between economics, institutional and cultural and social determinants.
• Knows how to apply statistical and machine-learning methods to analyse different types of socio-economic data
SKILLS
• Is able to analyze basic economic texts independently and critically.
• Is able to carry out the entire research process: he can independently put a research hypothesis, economic theory, adequate to the goal set in research work, can verify the research hypothesis, can search for data, apply the description of statistical or econometric modelling, can present in writing and pass the whole process as a thesis.
SOCIAL COMPETENCE
• Is critical of present economic problems and strives to rationally explain surrounding economic and social phenomena, learns to think, speak and write in a logical and consistent manner
• Thanks to individual work with the supervisor, he/she can properly determine the priorities in conducting research and writing work.
• By strengthening the motivation of the promoter, the student does not treat the master's thesis as a formal requirement, but as an element of personal and professional self-development
Assessment criteria
Every two months, each student is required to present progress in the work: personally, during the online call or by e-mail.
Bibliography
Materials selected individually fitted to a selected topic.
Shiller, R. J. (2020). Narrative economics: How stories go viral and drive major economic events. Princeton University Press.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: