Sentiment Analysis using Social Media Data

In this report, we will extract and analyze thousands of Twitter comments (tweets) using sentiment analysis algorithms in R.
This type of analysis could be useful to find business opportunities, make strategic decisions, improve products and procedures, etc. Note, that we can find more suitable sources of data to analyze these types of products, such as comments in forums, a list of reviews, other social networks, etc.

Let’s start by extracting and analyzing the “tweets” related to Nursing Schools during the last year: With the same data, it would be nice to plot a wordcloud to find correlated keywords:

Now, let’s extract and analyze tweets related to “Technology Schools” during the same period in the same language:

Below, in the wordcloud, we can find “Technology Schools” correlated keywords.

Additionally, to display a better comparison chart, we will extract twitter comments about “Therapist Schools”.

Below, in the wordcloud, we can find “Therapist School” correlated keywords.

Sentiment Analysis Comparision

Finally, we compare the 3 previous sentiment analysis together, so we can obtain a better understanding of every “school” performance.
Apart from these insights, it would be appropriate to use the same data to compare a competitor’s products or analyze how these values have changed over time.