Text Mining and Natural Language Processing in R from Udemy

Do You Want to Gain an Edge by Gleaning Novel Insights from Social Media?

Do You Want to Harness the Power of Unstructured Text and Social Media to Predict Trends?

Over the past decade there has been an explosion in social media sites and now sites like Facebook and Twitter are used for everything from sharing information to distributing news. Social media both captures and sets trends. Mining unstructured text data and social media is the latest frontier of machine learning and data science.

I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real-life data from different sources using data science-related techniques and producing publications for international peer-reviewed journals. Unlike other courses out there, which focus on theory and outdated methods, this course will teach you practical techniques to harness the power of both text data and social media to build powerful predictive models. We will cover web-scraping, text mining and natural language processing along with mining social media sites like Twitter and Facebook for text data. Additionally, you will learn to apply both exploratory data analysis and machine learning techniques to gain actionable insights from text and social media data.

Many courses use made-up data that does not empower students to implement R based data science in real life. After taking this course, you’ll easily use packages like the caret, dplyr to work with real data in R. You will also learn to use the common social media mining and natural language processing packages to extract insights from text data. I will even introduce you to some very important practical case studies - such as identifying important words in a text and predicting movie sentiments based on textual reviews. You will also extract tweets pertaining to trending topics analyze their underlying sentiments and identify topics with Latent Dirichlet allocation. With this Powerful course, you’ll know it all: extracting text data from websites, extracting data from social media sites and carrying out analysis of these using visualization, stats, machine learning, and deep learning.

Start analyzing data for your own projects, whatever your skill level and Impress your potential employers with actual examples of your data science projects.

Web-Scraping using R

Extracting text data from Twitter and Facebook using APIs

Extract and clean data from the FourSquare app

Exploratory data analysis of textual data

Common Natural Language Processing techniques such as sentiment analysis and topic modelling

Implement machine learning techniques such as clustering, regression and classification on textual data

Network analysis

Plus you will apply your newly gained skills and complete a practical text analysis assignment

We will spend some time dealing with some of the theoretical concepts. However, the majority of the course will focus on implementing different techniques on real data and interpreting the results.

After each video, you will learn a new concept or technique which you may apply to your own projects.

All the data and code used in the course has been made available free of charge and you can use it as you like. You will also have access to additional lectures that are added in the future for FREE.

What's inside

Learning objectives

Students will be able to read in data from different sources- including databases
Basic webscraping- extracting text and tabular data from html pages
Social media mining from facebook and twitter
Extract information relating to tweets and posts

Analyze text data for emotions
Carry out sentiment analysis
Implement natural language processing (nlp) on different types of text data

Students will be able to read in data from different sources- including databases
Basic webscraping- extracting text and tabular data from html pages
Social media mining from facebook and twitter
Extract information relating to tweets and posts
Analyze text data for emotions
Carry out sentiment analysis
Implement natural language processing (nlp) on different types of text data

Syllabus

INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools

About the Course and Instructor

Data and Scripts For the Course

Introduction to R and RStudio

Conclusion to Section 1

Reading in Data from Different Sources

Read in CSV & Excel Data

Read in Data from Online CSV

Read in Zipped File

Read Data from a Database

Read in JSON Data

Read in Data from PDF Documents

Read in Tables from PDF Documents

Conclusion to Section 2

(a) Learn more about web pages (b) Use the rvest package to extract text from different parts of an HTML page

Read in Data From Online Google Sheets

Read in Data from Online HTML Tables-Part 1

Read in Data from Online HTML Tables-Part 2

Get and Clean Data from HTML Tables

Read Text Data from an HTML Page

Introduction to Selector Gadget

More Webscraping With rvest-IMDB Webpage

Another Way of Accessing Webpage Elements

Conclusions to Section 3

Introduction to APIs

What is an API?

Extract Text Data from Guardian Newspaper

Extract Data from Facebook

Get More out Of Facebook

Set up a Twitter App for Mining Data from Twitter

Extract Tweets Using R

More Twitter Data Extraction Using R

Get Tweet Locations

Get Location Specific Trends

Learn More About the Followers of a Twitter Handle

Another Way of Extracting Information From Twitter- the rtweet Package

Geolocation Specific Tweets With "rtweet"

More Data Extraction Using rtweet

Locations of Tweets

Mining Github Using R

Set up the FourSquare App

Extract Reviews for Venues on FourSquare

Conclusions to Section 5

Exploring Text Data For Preliminary Ideas

Explore Tweet Data

A Brief Explanation

EDA With Text Data

Examine Multiple Document Corpus of Text

Brief Introduction to tidytext

Text Exploration & Visualization with tidytext

Explore Multiple Texts with tidytext

Count Unique Words in Tweets

Visualizing Text Data as TF-IDF

TF-IDF in Graphical Form

Conclusions to Section 6

Natural Language Processing: Sentiment Analysis

Wordclouds for Visualizing Tweet Sentiments: India's Demonetization Policy

Wordclouds for Visualizing Reviews

Tidy Wordclouds

Quanteda Wordcloud

Word Frequency in Text Data

Tweet Sentiments- Mugabe's Ouster

Tidy Sentiments- Sentiment Analysis Using tidytext

Examine the Polarity of Text

Examine the Polarity of Tweets

Topic Modelling a Document

Topic Modelling Multiple Documents

Topic Modelling Tweets Using Quanteda

Conclusions to Section 7

Text Data and Machine Learning

Clustering for Text Data

Clustering Tweets with Quanteda

Regression on Text Data

Identify Spam Emails with Supervised Classification

Introduction to RTextTools

More on Network Visualization

Analysis of Tweet Network

Identify Word Pair Networks

Network of Words

Text Analysis of Jane Austen's Mansfield Park

Miscellaneous Lectures

Github

Using R Within Google Colab

What Is Data Science?

Data Editing

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops skills and techniques for extracting text data and social media, which is a valuable skill for many roles in industry and research

Taught by Minerva Singh, a PhD with expertise in Tropical Ecology and Conservation and data science

Requires extensive background knowledge in data science and machine learning

Students are expected to have access to software

Develops professional skills and expertise on web-scraping, text-mining, and natural language processing

Teaches skills and knowledge used throughout industry and academia

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 Text Mining and Natural Language Processing in R with these activities:

Organize Your Notes, Assignments, and Recordings

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Maintaining an organized system for your course materials will facilitate efficient review and help you retain information better.

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Create a dedicated folder or notebook for the course
File notes, assignments, and recordings in a logical manner
Use headings, subheadings, and summaries to structure your notes
Consider using digital tools for organization and collaboration

Compile a List of Resources for Social Media Mining and Analysis

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Curating a compilation of resources will provide you with a valuable reference and help you stay up-to-date in the field.

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Identify relevant resources such as articles, tutorials, and tools
Organize the resources into categories for easy access
Include brief descriptions or annotations for each resource
Share your compilation with other students or interested individuals

Web Scraping Practice Exercises

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Strengthen your web scraping skills by solving practical exercises.

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Find a website or online resource.
Write a web scraping script to extract specific data from the website.
Test your script and refine it as needed.

Nine other activities

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Read 'Natural Language Processing with Python' by Steven Bird et al.

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This book provides a comprehensive overview of NLP techniques and will deepen your understanding of the concepts covered in this course.

View Natural Language Processing with Python:... on Amazon

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Read chapters relevant to the course topics
Work through the exercises and examples provided in the book
Implement some of the techniques described in the book in your own projects

Solve Practice Problems on Natural Language Processing

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Regular practice will reinforce your understanding of NLP algorithms and improve your problem-solving abilities.

Browse courses on Natural Language Processing

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Find practice problems online or in textbooks
Solve the problems using appropriate NLP techniques
Check your solutions and identify areas for improvement
Discuss your solutions with peers or participate in online forums

Explore the tidytext Library for Text Mining

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Familiarizing yourself with powerful libraries like tidytext will provide hands-on experience and enhance your text analysis skills.

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Install and import the tidytext library
Learn the basics of text manipulation and exploration
Practice cleaning and tokenizing text data
Explore techniques for creating and visualizing word clouds
Experiment with more advanced tidytext functions

Peer Study Group: Text Mining Techniques

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Collaborate with peers to reinforce text mining concepts and share insights.

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Form a study group with 2-3 peers.
Choose a topic related to text mining.
Each member presents their findings and leads a discussion.

Tutorial: Sentiment Analysis with Python

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Enhance your skills in analyzing and interpreting sentiments in social media text.

Browse courses on Sentiment Analysis

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Find a tutorial on sentiment analysis with Python.
Follow the tutorial step-by-step, implementing the code in your own Python environment.
Test the sentiment analysis model on your own social media data.

Build a Social Media Sentiment Analysis Dashboard

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Putting into practice your skills in social media mining and sentiment analysis by building a dashboard will help you solidify your understanding.

Browse courses on Sentiment Analysis

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Gather data from various social media platforms
Clean and pre-process the data
Perform sentiment analysis using appropriate techniques
Design and implement visualizations to display the sentiment analysis results
Deploy the dashboard and share your analysis

Write a Blog Post on Social Media Sentiment Analysis Techniques

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Explaining concepts to others through writing will solidify your understanding and enhance your communication skills.

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Choose a specific aspect of social media sentiment analysis
Research and gather information from reliable sources
Write a clear and engaging blog post explaining the techniques
Include examples and illustrations to support your explanations
Publish your blog post and share it with others

Social Media Analytics Workshop

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Deepen your understanding of social media analytics techniques in a hands-on setting.

Browse courses on Social Media Analytics

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Register for the workshop.
Attend the workshop and actively participate in the exercises.
Apply the techniques learned to analyze your own social media data.

Participate in a Kaggle Competition on Text Data Analysis

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Applying your skills in a competitive environment will challenge you to think critically and improve your problem-solving abilities.

Browse courses on Text Data Analysis

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Identify a relevant competition on the Kaggle platform
Read and understand the competition guidelines
Prepare your data and build a machine learning model
Submit your solution and track your progress
Analyze the results and learn from the experience

Career center

Learners who complete Text Mining and Natural Language Processing in R will develop knowledge and skills that may be useful to these careers:

NLP Engineer

An NLP Engineer designs, develops, and deploys natural language processing models. They can be responsible for building models that can perform tasks such as sentiment analysis, topic modeling, and text classification. This course can help you build a strong foundation in the fundamentals of NLP, and provide you with the skills you need to develop and deploy your own NLP models. The course also provides an introduction to social media mining, which can be helpful for NLP Engineers who want to work on projects that involve social media data.

See salaries and explore the career path for NLP Engineer

Data Scientist

A Data Scientist uses data to solve business problems. They can work on a variety of projects, such as developing predictive models, identifying trends, and understanding customer behavior. This course can help you build a strong foundation in the fundamentals of data science, and provide you with the skills you need to develop and deploy your own data science projects. The course also provides an introduction to social media mining, which can be helpful for Data Scientists who want to work on projects that involve social media data.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models. They can work on a variety of projects, such as developing predictive models, identifying trends, and understanding customer behavior. This course can help you build a strong foundation in the fundamentals of machine learning, and provide you with the skills you need to develop and deploy your own machine learning models. The course also provides an introduction to social media mining, which can be helpful for Machine Learning Engineers who want to work on projects that involve social media data.

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Software Engineer

A Software Engineer designs, develops, and deploys software applications. They can work on a variety of projects, such as developing new features for existing applications, or creating new applications from scratch. This course can help you build a strong foundation in the fundamentals of software engineering, and provide you with the skills you need to develop and deploy your own software applications. The course also provides an introduction to social media mining, which can be helpful for Software Engineers who want to work on projects that involve social media data.

See salaries and explore the career path for Software Engineer

Business Analyst

A Business Analyst studies business needs in order to identify opportunities for improvement, and develop innovative solutions. They may analyze data, or focus on strategy. This course can help build a foundation in data analysis, visualization and project management. It also provides an introduction to social media mining, which can be helpful for Business Analysts who want to work on projects that involve social media data.

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Research Scientist

A Research Scientist conducts research in a specific field of science. They can work on a variety of projects, such as developing new technologies, or studying the natural world. This course can help you build a strong foundation in conducting research and can help you develop skills in data analysis and visualization. The course also provides an introduction to social media mining, which can be helpful for Research Scientists who want to work on projects that involve social media data.

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Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical methods to solve problems in the financial industry. They can work on a variety of projects, such as developing trading strategies, or assessing risk. This course can help you build a strong foundation in the fundamentals of quantitative analysis, and provide you with the skills you need to develop and deploy your own quantitative models. The course also provides an introduction to social media mining, which can be helpful for Quantitative Analysts who want to work on projects that involve social media data.

See salaries and explore the career path for Quantitative Analyst

Data Analyst

A Data Analyst analyzes data in order to identify trends and patterns. They can work on a variety of projects, such as developing marketing campaigns, or identifying fraud. This course can help you build a strong foundation in the fundamentals of data analysis, and provide you with the skills you need to develop and deploy your own data analysis projects. The course also provides an introduction to social media mining, which can be helpful for Data Analysts who want to work on projects that involve social media data.

See salaries and explore the career path for Data Analyst

Product Manager

A Product Manager is responsible for the development and launch of new products. They work with engineers, designers, and marketers to bring new products to market. This course can help you build a strong foundation in the fundamentals of product management, and provide you with the skills you need to develop and launch your own products. The course also provides an introduction to social media mining, which can be helpful for Product Managers who want to work on projects that involve social media data.

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Marketing Analyst

A Marketing Analyst analyzes marketing data in order to identify trends and patterns. They can work on a variety of projects, such as developing marketing campaigns, or identifying customer behavior. This course can help you build a strong foundation in the fundamentals of marketing analysis, and provide you with the skills you need to develop and deploy your own marketing analysis projects. The course also provides an introduction to social media mining, which can be helpful for Marketing Analysts who want to work on projects that involve social media data.

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Social Media Manager

A Social Media Manager is responsible for the development and implementation of social media strategies. They can work on a variety of projects, such as developing content, or managing social media campaigns. This course can help you build a strong foundation in the fundamentals of social media marketing, and provide you with the skills you need to develop and implement your own social media strategies. The course also provides an introduction to social media mining, which can be helpful for Social Media Managers who want to work on projects that involve social media data.

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Content Writer

A Content Writer creates written content for a variety of purposes, such as marketing, advertising, or journalism. This course can help you build a strong foundation in the fundamentals of content writing, and provide you with the skills you need to develop and write your own content. The course also provides an introduction to social media mining, which can be helpful for Content Writers who want to work on projects that involve social media data.

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Web Developer

A Web Developer designs and develops websites. They can work on a variety of projects, such as developing new websites, or maintaining existing websites. This course can help provide you with the skills you need to develop and deploy your own websites. The course also provides an introduction to social media mining, which can be helpful for Web Developers who want to work on projects that involve social media data.

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Technical Writer

A Technical Writer creates technical documentation for a variety of purposes, such as user manuals, or software documentation. This course can help you build a strong foundation in the fundamentals of technical writing, and provide you with the skills you need to develop and write your own technical documentation. The course also provides an introduction to social media mining, which can be helpful for Technical Writers who want to work on projects that involve social media data.

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Librarian

A Librarian helps people find and access information. They can work in a variety of settings, such as public libraries, or academic libraries. This course can provide you with the skills you need to help people find and access information on social media. The course also provides an introduction to social media mining, which can be helpful for Librarians who want to work on projects that involve social media data.

See salaries and explore the career path for Librarian