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Textual Analysis using Python for HSS – Part IV in the HSS Python Series

a blue and purple triangle evoking a jet, aiming up and to the right. Text: ACENET; beneath: accelerate discovery

Event Language

English

Format

virtual/virtuel

Date: 27 November 2024

Description: This is a beginner-level 4-part series for humanities and social sciences (HSS) researchers (HSS) and librarians. API Querying & Textual Analysis – Parts III & IV focus on allowing participants to apply basic coding concepts to API querying and text-based analysis. We will use a Python library to analyze textual data and learn about common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, and more to explore meaningful trends in language patterns.


This is a continuation of the HSS Python Series. It is highly recommended that you complete the 2-part Python series, Introduction to Python & Coding for HSS – Part I & II in the HSS Python Series, before registering for API Querying and Textual Analysis. 

Technical requirements: Install Python using Anaconda. To run Python, we are going to use Jupyter Notebooks via JupyterLab. If you installed Anaconda, JupyterLab is installed on your system.