Develop your marketing strategy with Sentiment Analysis

A guide to discover the basics of the Sentiment Analysis, how to use it to improve your marketing and customer relations
4.0 (3 ratings) Instead of using a simple lifetime average, Udemy calculates a
course's star rating by considering a number of different factors
such as the number of ratings, the age of ratings, and the
likelihood of fraudulent ratings.
89 students enrolled
$40
Take This Course
  • Lectures 29
  • Contents Video: 1.5 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
Wishlisted Wishlist

How taking a course works

Discover

Find online courses made by experts from around the world.

Learn

Take your courses with you and learn anywhere, anytime.

Master

Learn and practice real-world skills and achieve your goals.

About This Course

Published 5/2015 English

Course Description

In this course we will learn about the uses of the sentiment analysis. The sentiment analysis is a part of textual analysis born in the last years, through the user comments analysis, and the use of tweets for predictive analysis. In this course we will discover the uses that can be made of sentiment monitoring, and how to use it to refine our marketing strategies.

In the first section we will learn how to structure your search, the data to extract, and how to use the sentiment for benchmarking and users analysis.

In the second section we will discover how to make the text normalisation, and in the third we will learn to use some tools for automatic analysis for sentiment in tweets and text.

The fourth section is focused on some special tools for the tweets analysis. We will also discover how to use Google spreadsheets to create a tweets database.

The fifth section is focused on user feedback analysis to improve your marketing strategies. 

The course ends with a section with some mixed tools that allow, in addition to some sentiment analysis, other kind of content analysis.

What are the requirements?

  • Students need to have online navigation and pc basic skills
  • Students should be familiar with basic marketing concepts

What am I going to get from this course?

  • discovering how to use the sentiment analysis of improve your business
  • how to use the sentiment analysis for the benchmark
  • normalise and prepare a text for the analysis
  • extract the customer comments from Disqus, Youtube, Facebook (public pages) and Amazon
  • extract tweets with Google sheets
  • learn about the most used software for the tweets analysis
  • learn about the tools to analyse not just tweets but all the comments

What is the target audience?

  • Students wanting to develop the skills necessary to improve a career in digital marketing,
  • Marketers, business owners, individuals
  • People having a business and wanting to achieve greater visibility and sales through SA

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
03:47

How the sentiment analysis was born: some data to start

06:03

How companies are used to use Sentiment analysis, the most important sources in text mining and the languages most used for research

02:14

For the Sentiment analysis, we can use automatic or manual processing. Let's see why

01:54

Sometimes is not enough to discover the text polarity, but the Sentiment analysis can be used for specific aims

00:46

Importance of categorization in the Sentiment Analysis

Content extraction vs opinion extraction
00:33
01:50

Use the Sentiment Analysis for brand reputation measuring

00:42

The sentiment analysis can also be used for benchmarking analysis between the same category products

01:56

There are various scales to measure sentiment, some are based on the simple distinction between positive and negative comments, some based on 5 or 7 point scale

04:15

Let's see what are the limits and the main problems of Sentiment analysis

01:50

The algorithms and machine learning for Sentiment analysis

Section 2: Steps and tools
02:58

How to normalize and clean a text for the analysis

Section 3: Sentiment analysis on text
03:24

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

01:45

Let's have a look in the Semantria demo

Sentiment Analysis with Sentistrenght
05:31
Section 4: Sentiment analysis on tweets
01:44

Tweet extraction and analysis with the site Sentiment140

01:40

Tweets and trending sentiment with Wordaffect

04:37

How extracting tweets with TAGS and Google Sheets

Section 5: Sentiment analysis on users feedbacks
00:57

Detect text sentiment with Text2data

API for Sentiment Analysis
04:08
01:15

One more tool for sentiment detecting

04:39

Building a database for Sentiment Analysis

Building a Twitter App
01:33
07:29

Let's start with Weka for Sentiment Analysis and csv files

09:52

Create an ARFF file with WEKA and apply the Sentiment Analysis

Section 6: Other tools
08:46

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

Vivekn
00:44
Section 7: Conclusions
Recap
02:49
Conclusions
00:51

Students Who Viewed This Course Also Viewed

  • Loading
  • Loading
  • Loading

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.

Ready to start learning?
Take This Course