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
  • Contents Video: 2 hours
    Other: 2 mins
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
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    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 4/2015 English

Course Description

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

What 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.

Curriculum

Section 1: Introduction
10:49

Introduction to the content analysis, text and data mining

06:00

Let's see the most important text analysis applications

03:28

How to normalize and clean a text for the analysis

01:21

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

Article

How to use text mining

Stemming and lemmatization
Article
Section 2: Qualitative methods for the content analysis
02:41

A quick introduction to software CAQDAS for the qualitative analysis

05:40

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

01:59

Download R and the IDE RStudio

09:08

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

09:06

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
03:41

Intro - statistics in text mining

04:37

How to extract tweets database with Google Sheets

Textalyser
01:27
00:41

A web based text analysis tool

07:27

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

02:53

Text overview, word cloud, concordances and graphics

03:59

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

06:18

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

03:24

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

05:49

Some example about text analysis on Python

Quantitative analysis
Article
Section 4: Tools for automatic categorisation
08:46

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

05:07

Dandelion categorizes text and extract concepts

Section 5: Word and tag clouds
02:28

Doing a word cloud with Wordle

01:08

Statics and dynamics tag cloud on the websites

01:01

Creating a word cloud with Manyeyes

01:56

Create a word cloud with Tagxedo

01:40

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

01:27

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

Section 6: Conclusions
Conclusions
01:15

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Instructor Biography

Valentina Porcu, Marketing Strategist and Data Analyst

Valentina is 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!

She works as consultant in the field of data mining and machine learning and she like writing about new technologies and data mining.

She spent the last 9 years working as freelance 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 startups and web agencies across UK, France, US and Italy.

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