fedenanni/Computational-Text-Analysis-2018-19
2018 Computational Text Analysis Notebooks, University of Mannheim
This collection of materials helps social scientists, humanities researchers, or anyone working with large volumes of text understand and apply computational methods. It guides users through transforming raw text data into structured insights, such as topic models or sentiment analysis, without needing advanced programming expertise from the outset. The primary users are researchers and students looking to analyze textual information for patterns and meaning.
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Use this if you are a researcher or student in social sciences or humanities who needs to apply computational methods to analyze text data and want a structured learning path.
Not ideal if you are looking for a ready-to-deploy, out-of-the-box text analysis application rather than learning the underlying methods.
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Nov 22, 2018
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