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Analysing Tweets using R

  • Development
  • Mar 23, 2025
SynopsisAnalysing Tweets using R, available at $54.99, has an average...
Analysing Tweets using R  No.1

Analysing Tweets using R, available at $54.99, has an average rating of 5, with 24 lectures, 4 quizzes, based on 2 reviews, and has 43 subscribers.

You will learn about Gathering Data from Twitter Using Twitter API Using Google Map API Analysing Twitter Data Lexicon based Emotion Analysis Use of many related R Libraries This course is ideal for individuals who are Students or Researchers or Data Analysts or Data Scientists or Computer Software Programmers It is particularly useful for Students or Researchers or Data Analysts or Data Scientists or Computer Software Programmers.

Enroll now: Analysing Tweets using R

Summary

Title: Analysing Tweets using R

Price: $54.99

Average Rating: 5

Number of Lectures: 24

Number of Quizzes: 4

Number of Published Lectures: 24

Number of Published Quizzes: 4

Number of Curriculum Items: 28

Number of Published Curriculum Objects: 28

Original Price: $129.99

Quality Status: approved

Status: Live

What You Will Learn

  • Gathering Data from Twitter
  • Using Twitter API
  • Using Google Map API
  • Analysing Twitter Data
  • Lexicon based Emotion Analysis
  • Use of many related R Libraries
  • Who Should Attend

  • Students
  • Researchers
  • Data Analysts
  • Data Scientists
  • Computer Software Programmers
  • Target Audiences

  • Students
  • Researchers
  • Data Analysts
  • Data Scientists
  • Computer Software Programmers
  • People around the globe make over 500 million tweets per day. So, one can only imagine the sheer volume of data available with Twitter. This data is a treasure trove of information. However, one needs to know how to gather this data and then conduct the needed analysis.

    This course provides all the information regarding

    1. How to gather data from Twitter using R Programming

    2. How to conduct basic analysis of the data gathered from Twitter

    3. How to extract the Emotion expressed in the Tweets gathered

    The course also discusses associated APIs required for analysing Twitter data like Google Maps API.

    To take full advantage of the course, it will be required to create a developer account with Twitter. All the necessary steps for getting a Twitter Developer Account is provided in the course. However, it must be noted that it is the discretion of Twitter whether they will grant a Twitter Developer account against an application. Nevertheless, all the contents of the course can be followed and understood without a Twitter Developer account. Only difference will be that the data extracted from Twitter will be restricted. With limited data, the analysis possible will be limited.

    We will use R Programming throughout this course. Thus, this course requires that the participants are conversant with R Programming.

    If you prefer any other programming language (like. Python, etc.), then you can use this course to learn all the nuances of analysing Twitter Data and apply the same in programming in your language of your preference.    

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Introduction

    Lecture 2: If you want to Learn R Programming or brush up on R Programming

    Chapter 2: Introduction to Twitter

    Lecture 1: What is Twitter and Why it is used?

    Chapter 3: Programming around Twitter

    Lecture 1: Twitter Developer Account

    Lecture 2: Fetching Tweets for Search String(s) and/or Hash Tag(s)

    Lecture 3: Getting Google Maps API Key

    Lecture 4: Fetching Tweets for a Location

    Lecture 5: Data fetched from Twitter

    Chapter 4: Displaying Information about the fetched Tweets

    Lecture 1: Displaying Fetched Tweets using DT

    Lecture 2: Creating Time Series Charts for the fetched Tweets

    Lecture 3: Basic Statistics – Introduction

    Lecture 4: Tweet Country Analysis

    Lecture 5: Tweet Place Analysis

    Lecture 6: Tweet Language Analysis

    Lecture 7: Tweet User Analysis

    Lecture 8: Tweet Source Analysis

    Lecture 9: Tweet Hash Tag Analysis

    Chapter 5: Programming Maps

    Lecture 1: Location Analysis with Maps

    Lecture 2: Interactive Maps with Leaflet

    Chapter 6: Emotion Analysis

    Lecture 1: Section Introduction

    Lecture 2: Extracting Words from fetched Tweets

    Lecture 3: Finding Most Prevalent Emotion

    Chapter 7: Course Closure

    Lecture 1: Next Steps

    Lecture 2: About Me (Optional)

    Instructors

  • Analysing Tweets using R  No.2
    Partha Majumdar
    Just a programmer
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  • Frequently Asked Questions

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