SENTIMENT ANALYSIS using shinyapp

The primary objective of this project is to enhance my knowledge of R and develop Exploratory Analysis & Visualization skills.

By this project I aim to review the learnings of Business Analytics Using R.

My Objective from this project is to understand shinyapp and its application to various sets of information from as may be required in real time.

In today's world, Social Media like FACEBOOK, TWITTER, etc. is every now and then used to express our feelings, given its potential to reach a large set of audience in no time.

Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.

This web app analyses the Sentiments in the text input by the user for its Polarity and Emotions expressed.

• It clasifies Polarity into:
  1. Positive 2. Negative 3. Neutral
     
• It clasifies Emotions into:
  
  1. Anger 2. Joy 3.Disgust 4.Fear 5. Surprise 6.Fear 7.Sad
     

This app perfroms Sentiment Analysis on each line as follows:

• Quantitative Analysis:
  Displays the Word Count, Line Count, Average Words per Line, Polarity Count and Emotion Count
  
• Qualitative Analysis
  
  1. Analyses Polarity and classifies into Positive, Negative and Neutral
     
  2. Analyses Emotions and classifies into Anger, Disgust, Fear, Joy, Sadness, Surprise, Unknown
     
• Visual Analytics:
  
  1. Displays Polarity count and Emotion count Histograms
     
  2. Word Cloud of Top 30 words

By the completion of this project, my primary objective of enhancing my knowledge of R & develop exploratory analysis & visualization skills has been met successfully, thus aiding me to draw top notch insights from the same…!

My Objective from this project to understand shinyapp and its application to various sets of information from as may be required in real time has also been met.

By this project I am able to review the the concept of Sentiment Analysis Using R, and moreover, the underlying logic and its relevant code.

To start with, experience of learning R was itself was an enthralling and exciting journey for me, given the technical expertise and support of such a wonderful faculty, and a gem of a person.

R equipped me for generating those visuals and conducting analyses.

Layout and basic commands of R, writing basic R scripts, and inspecting data sets using R, helped us in performing analytics, which would otherwise have been a tedious task using any other basic program like MS Excel or so…

Moreover, R building in data analysis functionality by default, helped me in performing Analytics faster and appropriately.