Sentiment Analysis is a type of text mining that is used to measure the attitudes, emotion or sentiments in a text. It can be used for a wide range of research topics such as assessing public perceptions of an event, monitoring emotion on social media, and analysing customer reviews and attitudes.

In this workshop we’ll look at Sentiment Analysis across disciplines, discuss strengths and limitations, and introduce common tools and procedures. Then we’ll look at an example using Python's NLTK (Natural Language Toolkit) with a model called VADER (Valence Aware Dictionary for Sentiment Reasoning).

Finally, we’ll do a hands-on activity to calculate sentiment for a paragraph of text using the programming language Python, Anaconda (an open source tool for organizing and setting up your Python environment), and NLTK. 

Pre-workshop setup

To make the most of the workshop activities please install Anaconda Navigator ahead of time following these instructions for your operating system: https://www.anaconda.com/products/individual.

This workshop is part of the Digital Humanities workshop series presented by the UBC Library Research Commons.

Location Details

Location:

*ONLINE*

If you have any questions, concerns, or accessibility needs please email eka.grguric@ubc.ca.

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