Table of Contents
- What is Constellate?
- How Do I Access Constellate?
- What is Text Analysis?
- How Can I Receive Training?
- Additional Resources
Constellate is a browser-based tool for creating datasets from collections, such as JSTOR, and then teaches and facilitates text analysis on those datasets.
Datasets are analyzed using python code run in Jupyter notebooks. Tutorials and sample code (that you can modify) help you get up and running quickly (with four short tutorials to get you started with python if that is new to you).
Not only can you teach yourself text analysis using python, Constellate provides How-To Guides (many aimed at teachers), and encourages using their materials to teach this in your classes.
While some parts of the Constellate site are available to everyone, the University of Toronto is participating in a special Beta Evaluation Period, meaning UofT users can take advantage of additional perks, such as being able to build larger datasets (up to 50,000 items) and take advantage of more computational power to run analyses. During this time, Constellate is working to improve their offerings, and so they are soliciting feedback. If you use Constellate in a teaching or research setting, please contact us with feedback, which we can anonymously pass on to them.
See this access tutorial to log into Constellate using full University of Toronto institutional permissions.
Text Analysis, using a tool such as Constellate, allows researchers to quickly analyze a large number of documents (more than a human could read, and faster). Some questions that can be answered using text analysis would be:
- What are these texts about?
- How are these texts connected?
- What emotions (or affects) are found within these texts?
- What names are used in these texts?
- Which of these texts are most similar?
These questions can be addressed using techniques such as finding word frequencies, performing topic modeling, or using sentiment analysis. Constellate tutorials can help you learn more about performing these tasks and answering these questions.
Synchronous (Live) Training
Constellate offers synchronous remote training. Here are links to their upcoming sessions, though please note that you must be logged in to view them:
- July 2021 Training: Build Your Own Class and Jupyter Notebook
- Prerequisite: Constellate recommends that attendees complete their Beginner lessons or be comfortable with Jupyter notebooks
- July/August 2021 Training: Introduction to Text Analytics
Constellate provides a video introduction at the start of each of their Beginner-level tutorials, walking you through the content.
In addition, if you sign into Constellate, you can access recordings of training sessions:
- March 2021 Recording: Introduction to Text Analytics
- April 2021 Recording: Build Your Own Class and Jupyter Notebook
- May 2021 Recording: Introduction to Text Analytics
Alternative to Constellate
If you prefer to work with a point-and-click interface without coding, please consider Gale’s Digital Scholar Lab. Like Constellate, it provides a number of sample collections, cleaning options, and text analysis tools. You can get started with our brief guide on accessing the Digital Scholar Lab, then either use the videos in the platform or follow our Digital Scholar Lab tutorial.
If you require help, either accessing Constellate or with its contents, please feel free to contact us at the Map & Data Library. You can either email firstname.lastname@example.org or reach out with the MDL contact form.
Constellate also offers office hours for Beta participants (including University of Toronto users). Here is the schedule of Constellate office hours.
There are a number of resources available at the University of Toronto for learning and working with tools for text analysis, as well as the broader field of text and data mining. If you would like to learn more, see this link.