Blog #13

Blog #11

 2 Oct 2017

In the last post we spoke about the difficulties and some of the solutions you can employ to improve your sentiment analysis implementation. In this post we'll talk about what's involved when you need to train your classifier.

Why do I need to train my classifier and how is this done?

In order for your classifier to accurately predict the probability of your text belonging to a specific category (in our use case positive / negative / neutral) you need to have datasets that are relevant to these categories.

Check out the following dataset and you'll see what I mean:

|positive|,|@PrincessSuperC Hey Cici sweetheart! Just wanted to let u know I luv u! OH! and will the mixtape drop soon? FANTASY RIDE MAY 5TH!!!!|

|positive|,|@Msdebramaye I heard about that contest! Congrats girl!!|

|positive|,|UNC!!! NCAA Champs!! Franklin St.: I WAS THERE!! WILD AND CRAZY!!!!!! Nothing like it...EVER|

|neutral|,|Do you Share More #jokes #quotes #music #photos or #news #articles on #Facebook or #Twitter?|

|neutral|,|Good night #Twitter and #TheLegionoftheFallen.  5:45am cimes awfully early!|

|neutral|,|I just finished a 2.66 mi run with a pace of 11'14"/mi with Nike+ GPS. #nikeplus #makeitcount|

|negative|,|Disappointing day. Attended a car boot sale to raise some funds for the sanctuary, made a total of 88p after the entry fee - sigh|

|negative|,|no more taking Irish car bombs with strange Australian women who can drink like head hurts.|

|negative|,|Just had some bloodwork done. My arm hurts|

Once you have your sample dataset you can load this into your classifier.  When you've configured and loaded your classifier you can then supply text to it for classification.  (If you want to see how this works "under the hood" I recommend checking out this article here as it breaks down numbers and talks about bayesian theorem).

If you'd like to know more, click the image below to Download our free Sentiment Analysis Whitepaper.

Or View Our Diary And Book In A Call

Also included in the Whitepaper:

  • An Introduction To Sentiment Analysis
  • Bayesian Theorem And It's Connection To Sentiment Analysis
  • The Difficulties Of Sentiment Analysis And It's Solutions
  • What Is POS Tagging And How Can You Use It?


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