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Exploring the RBMA lectures archive using text analysis and mining, with a focus on comparing Python and R processes and LDA-based topic modeling.

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This project uses tools and techniques introduced in the Digital Text in the Humanities course from the University of Bologna to undertake some basic text analysis and text mining, in the form of topic modeling, on a corpus made up of publicly available lecture transcripts from the Red Bull Music Academy series.

The raw data for the lectures is available at https://github.com/ewenme/rbma-lectures and the processed data generated during this project is included in the FILES folder. The transcripts themselves remain the property of Red Bull Media House and are used here for purely educational purposes.

Created and presented as part of the requirements for the Digital Text in the Humanities course within the Digital Humanities masters at the University of Bologna, academic year 2020-2021

Any comments or suggestions are welcome. Thanks for reading!

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Exploring the RBMA lectures archive using text analysis and mining, with a focus on comparing Python and R processes and LDA-based topic modeling.

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