Twitter Sentiment Analysis(TSA) - Online Retailers(2019-2021)

-

Project Overview:

Twitter Sentiment Analysis helps to understand the user experience of the online retailers based on the tweets, which is important for business development and product enhancement.This a online retailer problem so based on the tweets we are giving the rating of each customer about online shopping experience.

Sentiment analysis architecture: 



Approach for Twitter sentiment analysis of online retailers:

Scraping the tweets:

  1. Taking the tweets with respect to online retailers such as ebay, meesho, olx india, flipkart, amazon, jio mart. 
  2. After the extraction of the data from twitter, put into the data frame with respect to retailers. 
  3. Concatenating the data frame of each retailer into a single data frame. 
  4. Converting the data frame to CSV file. 

Data preparation and data cleaning:

  1. Importing the CSV file using pandas.
  2. Analyse & understand the nature of the data. 
  3. Tweets are not actual text format, it contains no text characters, writing a function to clean that and passing into the tweets data frame.

Modelling:

  1. Once the data is cleaned, we will use the hugging face nlp model to predict the sentiment of tweets and give the rating based on the expression. 
  2. Writing a function to apply the nlp model. 
  3. Creating a new column and apply nlp function to data frame and finding the rating 
  4. Removing the null value in the tweet column

Data visualisation:

  1. After finding the sentiment, count the rating of sentiment.
  2. Visualisualize the sentiment using Matplotlib.


Conclusion: 

From the fig, we conclude that most people usually prefer to buy online. This is due to Covid-19 and increasing mobile application & best user interface of some online retailer web and mobile applications. Enhancing the customer support of the online retailers helps in better production and sales. 

Comments

Post a Comment

Popular posts from this blog

Impact of Covid-19 on India

-
Image
Hi guys, this is my first blog toward data science!!!!! Introduction: Covid-19 or Coronovirus is a zoonotic disease which means its spread among animals and humans.India is the second most populous country, let's see how its spread and affect the people and their awarness about vaccination.  Impact of Covid-19: Unprepared lockdown which almost destroys the un organised sector. Lots of people lost their livelihood due to unemployment. Central government imposition of National lockdown affect the migration labour most of them crossed thousands of kilometers just by walking. Children's education is miserably affected. Mostly private school student are afford to online resources it create ineqauality in education and it affect basic structure of Indian constitution(Art-21A) Primary and Manufacturing sector are mostly affected which leads to reduction of GDP Total number of Positive cases: Total number of death cases: Inference from the Positive cases and death cases: Despite Mahara...
Read more

Best practice to follow on git and github

-
Some basics: linux Note: <> just used to differentiate the file for understanding : ls -list the file mkdir <folder name> - creach the file name touch <file name> - create the file code . - take to vs code vi <filename >- open the vim editor - Don’t dive deep into vim editor There are two mode Edit mode and command mode You can press Esc to enter cmd mode to give command like insert delete update and so on  i - for insert a text in a file O, o move the cursor above and below :wq - write and save the file These are the basic about vim editor but don’t spend too much time on this use other editor for faster progress and so on We can directly open the file and made the changes Vim is fun to learn cat <file name > - show what are there in that file rm -rf <file/folder name> -remove the the file or folder from the current directory cd - change the directory(where we are working and our file path) cd .. go back the previous folder in a directory Git c...
Read more

Deep learning with TensorFlow

-
Image
After learning the Sci-kit learn library, I started to think What, Where,  How should I start learning deep learning which library should go on, I find myself Tensorflow is easy to begin with because TensorFlow is developed by google and they providing a stable and extensive documentation and so on... While learning Image classification I came to know the power of GPU, Everything comes in colab which is very much handy. Main thing I learned about deeplearning is You can do anything as long as you can convert into object into Tensors (Array of numbers) Classification of 101 image of food data image data is done with EfficientnetB0 model using transfer learning. There I, learned the power of Transfer Learning. TensorflowHub providing various Pretrained model, we can use based on our need.  And there is something called Tensorboard whwere we can the evaluate the various model, we build with deeplearning. I attached the sample image of Tensorboard.  And there are so many reso...
Read more