We may earn an affiliate commission when you visit our partners.
Nicole Baerg
By the end of this project, you will be able to load textual data into R and turn it into a corpus object. You will also understand the concept of measures of readability in textual analysis. You will know how to estimate the level of readability of a text document or corpus of documents using a number of different readability metrics and how to plot the variation in readability levels in a text document corpus over time at the document and paragraph level.
Read more
By the end of this project, you will be able to load textual data into R and turn it into a corpus object. You will also understand the concept of measures of readability in textual analysis. You will know how to estimate the level of readability of a text document or corpus of documents using a number of different readability metrics and how to plot the variation in readability levels in a text document corpus over time at the document and paragraph level.
Read more
By the end of this project, you will be able to load textual data into R and turn it into a corpus object. You will also understand the concept of measures of readability in textual analysis. You will know how to estimate the level of readability of a text document or corpus of documents using a number of different readability metrics and how to plot the variation in readability levels in a text document corpus over time at the document and paragraph level.
This project is aimed at beginners who have a basic familiarity with the statistical programming language R and the RStudio environment, or people with a small amount of experience who would like to learn how to measure the readability of textual data.
Register for this course and see more details by visiting:
OpenCourser.com/course/fboiow/quantitative
What's inside
Syllabus
Project Overview
By the end of this project, you will be able to load textual data into R and turn it into a corpus object. You will also understand the concept of measures of readability in textual analysis. You will know how to estimate the level of readability of a text document or corpus of documents using a number of different readability metrics and how to plot the variation in readability levels in a text document corpus over time at the document and paragraph level.
This project is aimed at beginners who have a basic familiarity with the statistical programming language R and the RStudio environment, or people with a small amount of experience who would like to learn how to measure the readability of textual data.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for beginners with a basic understanding of statistical programming language R and the RStudio environment who want to learn to measure readability of textual data
Save this course
Save Quantitative Text Analysis and Measures of Readability in R to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Quantitative Text Analysis and Measures of Readability in R with these
activities:
Join a study group or online forum
Show steps
Connect with other learners to discuss the course material and exchange ideas.
Show steps
-
Find a study group or online forum related to the course.
-
Participate in discussions and ask questions.
Review basic statistical concepts
Show steps
Recall concepts like mean, median, mode, standard deviation, and variance to prepare for learning readability measures.
Browse courses on
Statistical Analysis
Show steps
-
Go over your notes from a previous statistics course or textbook.
-
Complete practice problems related to basic statistical concepts.
Follow a tutorial on the tidytext package
Show steps
Gain familiarity with the tidytext package for cleaning and analyzing textual data.
Show steps
-
Find a tutorial on the tidytext package.
-
Follow the steps in the tutorial to install the package and load data.
-
Experiment with the tidytext functions for cleaning and analyzing text.
Two other activities
Expand to see all activities and additional details
Show all five activities
Read "Text Mining with R"
Show steps
Deepen your understanding of text mining techniques and R programming.
View
Text Mining with R
on Amazon
Show steps
-
Read the book's chapters on text cleaning, analysis, and visualization.
-
Work through the book's exercises to apply the concepts you've learned.
Participate in a text analysis competition
Show steps
Challenge yourself to apply your skills in a competitive environment.
Browse courses on
Text Analysis
Show steps
-
Find a text analysis competition that aligns with your interests.
-
Build a model to solve the competition's task.
-
Submit your model and track your progress on the leaderboard.
Join a study group or online forum
Show steps
Connect with other learners to discuss the course material and exchange ideas.
Show steps
Show steps
Show steps
- Find a study group or online forum related to the course.
- Participate in discussions and ask questions.
Review basic statistical concepts
Show steps
Recall concepts like mean, median, mode, standard deviation, and variance to prepare for learning readability measures.
Browse courses on
Statistical Analysis
Show steps
Show steps
Show steps
- Go over your notes from a previous statistics course or textbook.
- Complete practice problems related to basic statistical concepts.
Follow a tutorial on the tidytext package
Show steps
Gain familiarity with the tidytext package for cleaning and analyzing textual data.
Show steps
Show steps
Show steps
- Find a tutorial on the tidytext package.
- Follow the steps in the tutorial to install the package and load data.
- Experiment with the tidytext functions for cleaning and analyzing text.
Two other activities
Expand to see all activities and additional details
Show all five activities
Read "Text Mining with R"
Show steps
Deepen your understanding of text mining techniques and R programming.
View
Text Mining with R
on Amazon
Show steps
Show steps
Show steps
- Read the book's chapters on text cleaning, analysis, and visualization.
- Work through the book's exercises to apply the concepts you've learned.
Participate in a text analysis competition
Show steps
Challenge yourself to apply your skills in a competitive environment.
Browse courses on
Text Analysis
Show steps
Show steps
Show steps
- Find a text analysis competition that aligns with your interests.
- Build a model to solve the competition's task.
- Submit your model and track your progress on the leaderboard.
Career center
Learners who complete Quantitative Text Analysis and Measures of Readability in R will develop knowledge and skills
that may be useful to these careers:
Computational Linguist
Computational Linguist
Computational Linguists use programming and data science to analyze language. With this course's focus on analyzing text, learners will build skills in analyzing and quantifying speech patterns and behaviors. This course can help build a foundation for a career in Computational Linguistics, which typically requires a PhD.
Lexicographer
Lexicographer
Lexicographers research and compile dictionaries. This course will teach learners how to analyze and quantify language, a valuable skill in lexicography. While a bachelor's degree is typically the minimum qualification, this course may be useful for learners interested in learning the foundations of Lexicography.
Speech-Language Pathologist
Speech-Language Pathologist
Speech-Language Pathologists (SLPs) work with people with speech and language disorders. This course will teach learners how to analyze and quantify language and behavior, essential skills for SLPs. While a master's degree is typically required, this course may be useful for learners looking to explore the SLP field.
Natural Language Processing Scientist
Natural Language Processing Scientist
Natural Language Processing (NLP) Scientists develop and implement NLP systems. This course will help build a foundation for NLP, which involves analyzing and quantifying text. While this field typically requires a master's or PhD, this course can help learners understand NLP.
Data Scientist
Data Scientist
Data Scientists use programming and data analysis to solve business problems. This course will teach learners how to analyze and quantify text and behaviors, a valuable skill in Data Science. While a master's or PhD is typically required, this course can help build a foundation for a career in Data Science.
Search Engine Optimizer
Search Engine Optimizer
Search Engine Optimizers (SEOs) help improve a website's visibility in search engine results. This course will help learners understand how to analyze and quantify text, an essential skill for SEO. While a bachelor's degree is typical, this course may be useful for learners looking to learn the fundamentals of SEO.
Digital Marketing Analyst
Digital Marketing Analyst
Digital Marketing Analysts research, plan, and execute marketing campaigns. This course will teach learners to analyze and quantify text, which is essential in digital marketing. This course may be useful for learners who wish to enter this field.
Web Developer
Web Developer
Web Developers design and develop websites. This course will teach learners to analyze and quantify language and behavior. While a bachelor's degree is typical, this course may be useful for budding Web Developers who wish to build a foundation in analyzing text.
User Experience Researcher
User Experience Researcher
User Experience (UX) Researchers study user behavior to improve product design. This course will teach learners how to analyze and quantify text and behavior, essential skills for UX Research. While a bachelor's degree is typical, this course may be useful for learners looking to learn the fundamentals of UX Research.
Information Architect
Information Architect
Information Architects design and organize website and intranet content. This course will teach learners how to analyze and visualize text, important skills for understanding user behavior. While a bachelor's degree is typically the minimum qualification, this course can help build a foundation for a career in Information Architecture.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts ensure that software meets standards and requirements. This course will help build skills in analyzing, quantifying, and reporting on data. While a bachelor's degree is typically the minimum qualification, this course may be useful for learners looking to learn the basics of Quality Assurance.
Social Media Manager
Social Media Manager
Social Media Managers create and manage social media content. This course will help build skills in analyzing and quantifying text and behaviors, essential skills in Social Media Management. While a bachelor's degree is typically the minimum qualification, this course may be helpful for learners looking to learn the basics of Social Media Management.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior. This course will help build skills in analyzing text and behavior. While a bachelor's degree is typically the minimum qualification, this course may be useful for learners looking to learn the basics of Market Research.
Linguist
Linguist
Linguists study human language and communication. This course will teach learners how to analyze and quantify text, essential skills in Linguistics. While a PhD is typically required, this course may be helpful for learners wanting to explore the foundations of Linguistics.
Data Analyst
Data Analyst
Data Analysts collect and analyze data to help businesses make informed decisions. This course will help build the foundation for analyzing and visualizing data, a key component of Data Analysis. While a bachelor's degree is typically required, this course may be useful for learners looking to learn basic techniques in Data Analysis.
For more career information including salaries, visit:
OpenCourser.com/course/fboiow/quantitative
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Quantitative Text Analysis and Measures of Readability in R.
Classic guide to writing clear and concise prose. It valuable resource for anyone who wants to improve their writing skills.
Modern guide to writing clear and concise prose. It valuable resource for anyone who wants to improve their writing skills.
Comprehensive guide to writing clear and concise prose. It valuable resource for anyone who wants to improve their writing skills. It is particularly useful for those who write in a professional context.
Practical guide to writing readable text. It provides clear and concise advice on how to improve your writing skills. It valuable resource for anyone who wants to write more effectively.
Practical guide to writing readable text. It provides clear and concise advice on how to improve your writing skills. It valuable resource for anyone who wants to write more effectively, particularly in a professional context.
Provides a practical guide to user experience design for small teams and individuals. It covers a wide range of topics, including user research, prototyping, and testing. It valuable resource for anyone who wants to learn more about user experience design and how to use it to improve the user experience of their products.
Provides a comprehensive overview of user experience design, including a discussion of the different elements of user experience and the different methods that can be used to design user experiences. It valuable resource for anyone who wants to learn more about user experience design and how to use it to improve the user experience of their products.
Provides a practical guide to web usability. It covers a wide range of topics, including user research, information architecture, and design. It valuable resource for anyone who wants to learn more about web usability and how to use it to improve the usability of their websites.
Provides a comprehensive overview of design, including a discussion of the different principles of design and the different methods that can be used to design products. It valuable resource for anyone who wants to learn more about design and how to use it to improve the user experience of their products.
Provides a practical guide to understanding people, including a discussion of the different factors that influence how people think and behave. It valuable resource for anyone who wants to learn more about human behavior and how to use it to improve the user experience of their products.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/fboiow/quantitative
Share
Similar courses
Here are nine courses similar to
Quantitative Text Analysis and Measures of Readability in R.
Quantitative Text Analysis and Scaling in R
OpenCourser.com/course/gjeo2u/quantitative
Quantitative Text Analysis and Scaling in R
Most relevant
Quantitative Text Analysis and Textual Similarity in R
OpenCourser.com/course/tl2mse/quantitative
Quantitative Text Analysis and Textual Similarity in R
Most relevant
Quantitative Text Analysis and Evaluating Lexical Style in R
OpenCourser.com/course/5q0p7q/quantitative
Quantitative Text Analysis and Evaluating Lexical Style...
Most relevant
Introduction to Text Classification in R with quanteda
OpenCourser.com/course/js7sdz/introduction
Introduction to Text Classification in R with quanteda
Most relevant
Introduction to Sentiment Analysis in R with quanteda
OpenCourser.com/course/nexh7x/introduction
Introduction to Sentiment Analysis in R with quanteda
Most relevant
Exploratory Data Analysis with Textual Data in R / Quanteda
OpenCourser.com/course/w8f5qw/exploratory
Exploratory Data Analysis with Textual Data in R /...
Most relevant
Analyze Text Data with Yellowbrick
OpenCourser.com/course/cbemvc/analyze
Analyze Text Data with Yellowbrick
Public Engagement for Scientists
OpenCourser.com/course/isgzqn/public
Public Engagement for Scientists
Get Started with R Markdown
OpenCourser.com/course/37l420/get
Get Started with R Markdown
Effort
1 hour
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Nicole Baerg
Language
English
Good to know
Suitable for beginners with a basic understanding of statistical programming language R and the RStudio environment who want to learn to measure readability of textual data
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser