Text mining and content analysis

A guide to start with the text and content analysis with quantitative and qualitative tools
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  • Lectures 32
  • Length 2 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 4/2015 English

Course Description

Attention please, the course will be completely reviewed in the next weeks! If you want to buy it, please, come back or be patient! Thanks :)

This course is for whoever who want to know the basics of text and content analysis. In the first section, after a general introduction on the analysis of texts, we will see how textual data are used by companies to improve internal performance, customer relations and benchmarking. Then, we will see how to perform text normalisation for the data analysis.

In the second section we will learn about the qualitative analysis, and the most known and easy to use CAQDAS software.

In the third section we will learn about the use of automatic and semi-automatic tools for the text analysis, and some quick tools for textual statistics as well as some hints on the conversation analysis and sentiment analysis.

The fourth section is focused on the automatic categorisation, concepts extracting and images recognition.

Finally, in the fifth part you will find some of the most widely used software for creating beautiful word clouds and tree clouds.

What are the requirements?

  • in this course you will learn to analyse your text data with free or freemium tools

What am I going to get from this course?

  • start with the text and content analysis
  • discover the companies' applications
  • learn the data used in the content analysis
  • explore the qualitative analysis basics
  • normalise a text for analysis
  • use the tools of the content analysis
  • learn about the automatic categorization
  • do beautiful word clouds and tree clouds

Who is the target audience?

  • learn about text mining and content analysis
  • discover how to use this kind of data

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.


Section 1: Introduction

Introduction to the content analysis, text and data mining


Let's see the most important text analysis applications


How to normalize and clean a text for the analysis


A basic tool for the text normalization: change the text in lowercase with Wordcounttools


How to use text mining

Stemming and lemmatization
Section 2: Qualitative methods for the content analysis

A quick introduction to software CAQDAS for the qualitative analysis


How to use QDA miner lite to do some qualitative text analysis and coding management


Download R and the IDE RStudio


Using the package RQDA (for R) for the qualitative analysis


Some softwares for qualitative analysis not only allow text analysis, but also video and photo coding. Let's have a look into Atlas

1 page

Qualitative softwares comparison chart

Section 3: Quantitative methods

Intro - statistics in text mining


How to extract tweets database with Google Sheets


A web based text analysis tool


An online tool to analyze statistics file text, HTML and XML


Text overview, word cloud, concordances and graphics


Yoshikoder allows quantitative text analysis, allowing to categorize text and use some statistical functions


A brief introduction to the sentiment analysis techniques. One of the most promising techniques for text analysis in the last years is the sentiment analysis, that allows brand and product analysis, customer satisfaction measuring and benchmark analysis


How to use the site text-processing for stemming and measure the text sentiment


Some example about text analysis on Python

Quantitative analysis
Section 4: Tools for automatic categorisation

Meaningcloud categorizes and analyzes texts from the console or through the Excel extension for Windows


Dandelion categorizes text and extract concepts

Section 5: Word and tag clouds

Doing a word cloud with Wordle


Statics and dynamics tag cloud on the websites


Creating a word cloud with Manyeyes


Create a word cloud with Tagxedo


Get2gist allows to visualise the co-occurences in a word cloud


With treeclouds you can visualise the keyword clusters in a text and building a beautiful tree cloud

Section 6: Conclusions

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Instructor Biography

Valentina Porcu, Marketing Strategist and Data Analyst

I'm a computer geek, data mining and research passionate, with a Ph.D in communication and complex systems and years of experience in teaching in Universities in Italy, France and Morocco, and online, of course!

I work as consultant in the field of data mining and machine learning and I like writing about new technologies and data mining.

I spent the last 9 years working as freelance and researcher in the field of social media analysis, benchmark analysis and web scraping for database building, in particular in the field of buzz analysis and sentiment analysis for universities, startups and web agencies across UK, France, US and Italy.

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