Text Mining with R (From Top Keywords to Sentiment Analysis)

This is a lecture where we will step-by-step explore top keywords, word clouds, sentiment analysis, and topic modeling using R.

(4.3) 11 reviews

302 learners

Level Basic

Course period Unlimited

R
R
Web Crawling
Web Crawling
Text Mining
Text Mining
R
R
Web Crawling
Web Crawling
Text Mining
Text Mining

Reviews from Early Learners

Reviews from Early Learners

4.3

5.0

Hyejin Kwon

100% enrolled

Actually, it's good to do it while practicing together, but it was difficult to follow along at the same time when I was still immature. But I think it would be good to watch it repeatedly. I think it was an important lecture because there aren't many places where you can listen to Korean text analysis, especially topic and sentiment analysis, online. I think I'll understand it a little better and be able to use the code directly if I watch it one more time. And it was really good that they gave me all the code in advance as materials.

5.0

아쿠아라이드

100% enrolled

As someone who studies R machine learning and applies it to my work, I think this is the best cost-effective lecture that can help me understand not only text mining but also the overall machine learning concept, and improve my R coding skills, and that can simultaneously capture both practical applicability and skill improvement. The last lecture, LDA, was a bit difficult, but... If I ever need a similar analysis later, I think I can watch the lecture again and apply it~~ I would like to express my gratitude to the instructor for providing such a high-quality lecture at a very low price... I will see you again in the next lecture. ㅎㅎ

5.0

DT로

100% enrolled

I also analyzed keywords while performing reports and work and organized them into important keywords. It was a good class to learn about the numerical factors of machine learning through sentiment analysis. I recommend it.

What you will gain after the course

  • How to perform morphological analysis

  • Extract Top Keywords

  • How to draw a beautiful Wordcloud

  • Sentiment Analysis

  • Topic Modeling(LDA)

Let's create jewel-like information
from the pouring sea of data! 💎

What is text mining? 🤔

Text mining is the process of mining unstructured data. Mining is a process of extracting statistically significant concepts and deriving information through patterns between them. Among these, text mining refers to mining using unstructured data such as videos, messages, and location information. However, because unstructured data has no fixed format, data collection is difficult.

In this lecture, you can learn how to handle unstructured data, which is becoming increasingly important due to the growth of social media!


What will I learn? 📖

1. Top Keyword Extraction / Drawing a Beautiful WordCloud

Learn about the morphological analyzer KoNLP, extract top keywords, and create a word cloud.



2. Try Dictionary-based/Machine Learning Sentiment Analysis

We will explore how to perform sentiment analysis by building a custom dictionary and by using regression analysis (machine learning).

What is Sentiment Analysis?

Sentiment Analysis is a process of quantifying and analyzing subjective information, such as emotions or opinions embedded in text, based on words and context. Sentiment analysis is actively used in business, such as listening to consumers' opinions about products or services and utilizing them. Sentiment analysis is also a type of text mining technology.

3. Topic modeling


Related Lectures 🖋️

<Web Crawling with R - Introductory>

  • You can learn basic crawling techniques.
  • It is recommended to study this before taking this course.
  • Click on the image to go to the corresponding lecture.

Frequently Asked Questions 🙋‍♀️

Q. Can non-majors take this course?

The lecture proceeds on the assumption that you have basic knowledge of the R language. Those who have taken Introduction to Web Crawling with R will be able to follow along without any problems.

Recommended for
these people

Who is this course right for?

  • Those who want to do text mining with R

  • Those who have taken the crawling course

Hello
This is coco

8,459

Learners

517

Reviews

136

Answers

4.4

Rating

20

Courses

I am an unemployed scholar who majored in statistics as an undergraduate, earned a PhD in industrial engineering (artificial intelligence), and is still studying.

Awards ㆍ 6th Big Contest: Game User Churn Algorithm Development / NCSOFT Award (2018) ㆍ 5th Big Contest: Loan Delinquency Prediction Algorithm Development / Korea Association for ICT Promotion

Awards

ㆍ 6th Big Contest Game User Churn Prediction Algorithm Development / NCSOFT Award (2018)

ㆍ 5th Big Contest Loan Defaulter Prediction Algorithm Development / Korea Association for ICT Promotion (KAIT) Award (2017)

ㆍ 2016 Weather Big Data Contest / Korea Institute of Geoscience and Mineral Resources President's Award (2016)

ㆍ 4th Big Contest: Development of Insurance Fraud Prediction Algorithm / Finalist (2016)

ㆍ 3rd Big Contest Baseball Game Prediction Algorithm Development / Minister of Science, ICT and Future Planning Award (2015)

* blog : https://bluediary8.tistory.com

My primary research areas are data science, reinforcement learning, and deep learning.

I am currently doing crawling and text mining as a hobby :)

I developed an app called Marong that uses crawling to collect and display only popular community posts,

I also created a restaurant recommendation app by collecting lists of famous restaurants and blog posts from across the country :) (it failed miserably..)

I am currently a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting blog posts and lists of top-rated restaurants across the country :) (though it failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

More

Curriculum

All

13 lectures ∙ (4hr 10min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

11 reviews

4.3

11 reviews

  • softjara0875님의 프로필 이미지
    softjara0875

    Reviews 10

    Average Rating 5.0

    5

    100% enrolled

    I have already signed up for and am listening to 4 of the instructor's lectures. It is very helpful for understanding text mining and sentiment analysis in R. However, the only regret is that I am distracted because I have to copy the code while coding and go back and forth between the execution screens. It would be better if the instructor explained it after editing it. ^^

    • hjsjforever5083님의 프로필 이미지
      hjsjforever5083

      Reviews 3

      Average Rating 5.0

      5

      100% enrolled

      Actually, it's good to do it while practicing together, but it was difficult to follow along at the same time when I was still immature. But I think it would be good to watch it repeatedly. I think it was an important lecture because there aren't many places where you can listen to Korean text analysis, especially topic and sentiment analysis, online. I think I'll understand it a little better and be able to use the code directly if I watch it one more time. And it was really good that they gave me all the code in advance as materials.

      • aquarid22님의 프로필 이미지
        aquarid22

        Reviews 12

        Average Rating 5.0

        5

        100% enrolled

        As someone who studies R machine learning and applies it to my work, I think this is the best cost-effective lecture that can help me understand not only text mining but also the overall machine learning concept, and improve my R coding skills, and that can simultaneously capture both practical applicability and skill improvement. The last lecture, LDA, was a bit difficult, but... If I ever need a similar analysis later, I think I can watch the lecture again and apply it~~ I would like to express my gratitude to the instructor for providing such a high-quality lecture at a very low price... I will see you again in the next lecture. ㅎㅎ

        • psangkuk6551님의 프로필 이미지
          psangkuk6551

          Reviews 4

          Average Rating 5.0

          5

          100% enrolled

          I also analyzed keywords while performing reports and work and organized them into important keywords. It was a good class to learn about the numerical factors of machine learning through sentiment analysis. I recommend it.

          • geonhee2720836님의 프로필 이미지
            geonhee2720836

            Reviews 3

            Average Rating 5.0

            5

            100% enrolled

            This is such a great lecture!! I want to listen to Coco's lecture again. I definitely want to listen to the next lecture too.

            • coco
              Instructor

              Thank you always for the great review. I hope it helps :)

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