Analyze Interview Transcripts for Individual Speaker Grade Levels w/ Python

Опубликовано: 29 Сентябрь 2024
на канале: Too Long; Didn't Watch Tutorials

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Dive into the world of qualitative research and analytics with this brief tutorial on analyzing interview transcripts. Specifically, you'll learn how to import a set of interview transcripts, separate each speaker in the transcript and apply a Flesch-Kincaid Grade Level score to each individual's responses using Python.

Whether you're a researcher, student, or simply curious about qualitative data analysis, this tutorial is tailored for you. We'll start with the basics of qualitative analysis, discussing its importance and applications. Then, we'll delve into the practical side, where you'll see Python in action as it calculates grade level scores for each interviewee's responses. The Flesch–Kincaid Grade Level formula presents a score as a U.S. grade level, making it easier for teachers, parents, librarians, and others to judge the readability level of various books and texts. It can also mean the number of years of education generally required to understand a set of text.

🐍 What You'll Learn:

- Creating a Python file from scratch and importing necessary modules
- How to import all transcripts in your folder with Microsoft Word format (.docx)
- How to separate each individual speaker in the transcript
- How to implement the Flesch-Kincaid Grade Level score in Python using the Textstat module

This tutorial is designed for learners at all levels - no prior experience in qualitative analysis or Python programming is required. By the end of this video, you'll be equipped with the skills to perform insightful transcript analysis and readability assessments, enhancing the depth and accuracy of your research or projects.

I want to reiterate that different implementations of the Flesch-Kincaid Grade Level score can generate slightly different scores. For example, some integrate modifications that put more weight on capitalization and punctuation, whereas others do not. However, my goal in this video is to identify the relative differences in grade levels between all speakers in the transcript. Therefore, as long as you use the same implementation (in this case, Textstat) when comparing grade levels, you should be fine!

Please note that this can also be done with .doc, .txt, or .pdf files as well, you would just need a different module to import these. Please let me know if you have questions.

Thanks for watching!

Link to code: https://github.com/TLDWTutorials/Fles...

TIMELINE

Intro - 0:00
Overview - 0:06
Getting started creating Python file/importing modules - 1:18
Quick review of transcripts we are importing - 1:54
Begin writing/covering Python script - 2:49
Running the script - 5:22
Side by side view of Transcript 2 and results - 6:00
Summarizing - 6:35
Outro - 7:02