Project whose the aim is to capture Social Network posts and extract the feeling from them. To this end, the program will collect data from social networks given some user choices (as a topic to search on Twitter), store, treat and model seeking to identify the feeling expressed in the post as positive or negative. Different sentiment analysis techniques will be tested to seek the best result.

• At the prompt:
  • run pip install -r requirements.txt to install the requirements in your environment
  • python -m spacy download en_core_web_sm to downoad the portuguese available core model. To see about other models, visit spacy.
• visit twitter-develop and create a Twitter account if you don’t have one. You’ll need to generate access keys and add them to the file api/configs.ini
• Running:
  • the program so far has two input variables, all of which are optional. They are: hashtag you want to search on Twitter and number of posts you want to collect. The default is: whitehouse, 200, respectively.

• Create functions to pre-process the data
• Create the method input variable to allow the collection, pre-processing and modeling steps to be run separately
• Create sentiment analysis models and apply on a pre-processed data

• Cássio de Alcantara – cassio-all
• João Lucas Flauzino Cassiano – joaoflauzino

See also the list of contributors who participated in this project.