Methodological Approaches to Computational History Research

This exam investigates the methodologies employed in computational history research, emphasizing techniques such as text mining, sentiment analysis, and network analysis. Candidates are expected to articulate the relevance and application of these methods in confirming or challenging traditional historical narratives.

Methodological rigor in computational history is vital for producing reliable and impactful research that contributes significantly to historical scholarship. Understanding these approaches facilitates a more comprehensive engagement with historical sources and their contextual significance.

The exam will evaluate the candidate's proficiency in discussing various methodologies, including their strengths and limitations when applied to historical texts and data sets, emphasizing critical thinking and analytical skills.

Candidates should be prepared to provide specific examples of methodological applications and discuss how these practices can yield new insights into historical phenomena.