Text Analytics Skills

If you are working as a Data Analyst or a Data scientist as I do, or if you are learning to be one, You should be familiar with the fact that data comes at a breakneck speed and Data Scientist and Analysts are meant to handle the data that is most numerical and categorical. But today, Data Scientists are more considered about Text Analytics as the majority of the data business is getting is based on text such as books, articles, website text, blog posts, social media posts, etc.

Today a company makes most of the decisions based on widely used keywords, keyphrases provided by the internet, partners, customers about the frequency of the keywords that are being used the most. The reason behind I am writing this post is that I want to make you understand what the idea behind text analytics is.

Master Text Analytics Skills

Hacker News is one of the best sites to know technology and startup news. So, In this article, I will introduce you to how to perform text analytics on Social News in as much as the simple way I can make you understand by presenting some initial results, and I will also try to guide you where you can take it next.

Simple Text Analytics

For Text Analytics, the dataset I got includes over 1 million news articles from September 2013 to Jone 2017. Now I will show you what I got as the most common words that were used in the titles of the articles.

text analytics
Most Used Words in Title

The above analysis shows the most frequent words that were used in titles between 2013 to 2017.

Now let’s analyze this most simply. In the figure above, you can see the most used word as “hn,” which is mainly used in “ask hn,” “show hn,” or some other words like that. Then the next frequent words include “Google,” “data,” “app,” which is quite expected in the titles of a news website.

Now, how to apply the results of this type of text analytics in your business? It’s simple; you need to go through those websites which are already doing more the best in the same field where you work. If you analyze the most used words in their title, you could be the next soon.

Simple Sentiment Analysis

Now let’s move to the most used application of text analytics which is Sentiment Analysis. Sentiment Analysis analyses the text to convert whether the sentiments of the text are positive or negative. It is used to make a conclusion that how people react to your actions, services, products, reviews, and more. Sentiment analysis are done by the total word counts of each sentiment and analyzing what things people don’t like.

sentiment analysis

In the figure above we can find some keywords that are coming out as a problem for the website. The words in the red above are the keywords where people have given a negative response to your articles, and the blue ones indicate those keywords, on which people who have given positive feedback to your articles.

Also, read – 10 Machine Learning Projects to Boost Your Portfolio.

Now after analyzing, these sentiments, we can apply these on our business by not focusing on those articles which are not liked by the visitors or our customers to improve the ratings of our business.

I hope you liked this article on Mastering your Text Analytics skills. Once you get capabilities to analyze text then you can easily apply the results in your business. Feel free to ask your valuable question on this article or any other that you want in the comments section below.

Also, read – Sales Forecasting for Next 50 Weeks with Time Series.

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Aman Kharwal

I am a programmer from India, and I am here to guide you with Data Science, Machine Learning, Python, and C++ for free. I hope you will learn a lot in your journey towards Coding, Machine Learning and Artificial Intelligence with me.

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