Introduction to Text Analytics with R Part 1 | Overview | Video

This data science series introduces the viewer to the exciting world of text analytics with R programming. As exemplified by the popularity of blogging and social media, textual data if far from dead – it is increasing exponentially! Not surprisingly, knowledge of text analytics is a critical skill for data scientists if this wealth of information is to be harvested and incorporated into data products. This data science training provides introductory coverage of the following tools and techniques:

– Tokenization, stemming, and n-grams
– The bag-of-words and vector space models
– Feature engineering for textual data (e.g. cosine similarity between documents)
– Feature extraction using singular value decomposition (SVD)
– Training classification models using textual data
– Evaluating accuracy of the trained classification models

READ ALSO:  Tutorials for High School Mathematics: Scientific Notation: Computation | Video

The overview of this video series provides an introduction to text analytics as a whole and what is to be expected throughout the instruction. It also includes specific coverage of:

– Overview of the spam dataset used throughout the series
– Loading the data and initial data cleaning
– Some initial data analysis, feature engineering, and data visualization

READ ALSO:  Classical and Quantum statistics in hindi || Raj Physics tutorials #physics #science | Video

Kaggle Dataset:

The data and R code used in this series is available here:

Learn more about Data Science Dojo here:

Watch the latest video tutorials here:

See what our past attendees are saying here:

Like Us:
Follow Us:
Connect with Us:

Also find us on:

#rprogramming #textanalytics #rtutorial



  1. hey @Dave getting this as error
    package or namespace load failed for ‘quanteda’ in loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]]):

    namespace ‘rlang’ 0.4.2 is already loaded, but >= 0.4.3 is required
    please help me out here please

  2. Thank you for your contribution for the world David! you are amazing and your parents are proud of you.

  3. what if i want to exclude stop words from stop_words() list how can i do it? i tried to to make custom stopwords but it didn't work.

  4. Dave, I've done several trainings during my career, both online and in-person, and I can assure you that your teaching style is the best I've ever known. Congratulations, you have the gift. Well done!

  5. Does this series of videos give me the path to learn about extracting complex data in PDF file and then analysing them?

    Sir, please do reply

  6. pls i am getting this error "Error in socketConnection(port = port, server = TRUE, blocking = TRUE, : cannot open the connection" when i run "cl <- makeCluster(3, type = "SOCK")" on my laptop

  7. Nice explanation. But one small question " how does it differentiate spam & ham data? , because everything we took is raw data & all are messages only here" . Thanks in advance.

  8. This might be a silly question, but if you've installed ggplot or dplyr or any other package in a previous analysis (on the same machine), do you have to reinstall it EVERY time you want to use it? Or can you just install a bunch of packages once and then never have to do it again? Thanks for your videos, btw. I landed a pretty significant interview by watching these!

  9. Hello Sir, I have a request, Can i use your code and the learning and demonstrate this whole in Bengali language and upload it, am I allowed to that. There are a lot of people who use this language and might be helpful for them to understand. As you know helping some one to understand in there mother tongue is the best way to teach.

    Thank You

  10. Hi

    if i want search one word in one location in twitter, how i do??

    i used this code
    cand <- searchTwitter('WORD', n = 100 ,since="2014-05-06", until="2018-05-06" , geocode="-23.55052,-46.63331,km")

    run, search the word but not in one location especific….

  11. 1.

    spam.raw <- read.csv("spam.csv",stringsAsFactors = FALSE)

  12. Hi Dave, thank you so much for the great content. It really help me a lot of data analysis.
    I recommend everyone else watch Dave's other videos especially the introduction to data science series. Very informative and easy to understand. Happy holiday.

  13. everything stops working as soon as I run:

    "spam.raw <- read.csv("spam.csv", stringsAsFactors = FALSE, fileEncoding = "UTF-16")"

    anyone else facing same problem?

  14. Great video. I'm from Brail, and my level of English is beginner. but his teaching is very good, and I understood the idea and examples well. Thank you. I signed the Channel and left my like! A "hello" from Brazil to you!

  15. Hi I am facing an issue. When I pass this command, spam.raw$TestLength <- nchar(spam.raw$Text) the entire row with text length reads 1000 for some wierd reason. Plus summary says Length 0, Class Null Mode Null. Can some one explain how to get this running?

  16. Wonderful video sir.. Do you have any lecture or material on unsupervised text analytics as well? unsupervised when I mean it is I have lots of server log and want to make some sense of out it.

Comments are closed.