AdOpinion

A minimalistic advertisement algorithm powered by Sentiment Analysis

The app schema/topology

What it does

It call the Twitter API and fetch the 300 last tweets concerning the brand entered in the search bar (the number of tweets can be modified). Then it analyses these tweets and classify them into 'positive' or 'negative' ones using a trained model (best_model.hdf5) based on a bidirectionnal LSTM network. Finally, it outputs the list of the 'positive users' and the 'negative users' : the 'positive users' are those who 'likes' the brand so a marketing service of this brand may be interested in sending product advertisements to them because they know that they will buy it. On the other side, the 'negative users' will be more excited to watch the 'moral value video' of the brand because those are potential users...

Thus, it target users based on their sentiment and not according some cookies statistics.

Installation

• Register in https://developer.twitter.com/ then create an application in the developer console and generate the API keys : consumer_key, consumer_secret, access_token_key and access_token_secret.
• Copy/paste those keys in the model.js(AdOpinion/routes/model.js) in the associated field.
• Install node
• Then, enter in the terminal : git clone https://github.com/gabrielmougard/AdOpinion.git && cd AdOpinion && npm install
• Run pip3 install -r requirement.txt to install python3 dependencies.
• Install some dictionnaries : type python3 in a terminal then enter in the interpreter : import nltk and nltk.download() then type d and enter the following keywords : stopwords, punkt, averaged_perceptron_tagger, wordnet.
• Finally, execute npm start in the same terminal and open your web browser where you can type localhost:3000 to open the platform !

Important note

• Wait a little bit when you want to click on the two buttons because you have to wait for the predictions (10s max)!

Cheers !