The objective is to predict the sentiment for texts contained in the test dataset, given the text and drug name.
Companies are constantly looking out across various platforms, such as blogs, forums, social media, etc. for checking the sentiment around their various products and also competitor products to learn how their brand resonates in the market.This analysis helps them in various aspects of their post-launch market research and is relevant for a lot of industries, including pharma and their drugs. The solution applied here is a NLP based approach which can be understood through the code mentioned in the repository.
The data source was AnalyticsVidhya where the data contains samples of text. This text could potentially contain one or more drug mentions. Each row contained is a unique combination of the text and the drug mention. Note: The same text could also have different sentiments for a different drug.
Environment : Python3
- Keras
- Numpy
- Tensorflow
- Pandas
- Nltk
- String