cbaziotis/datastories-semeval2017-task4
Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".
This project helps social media analysts or brand managers understand public opinion by analyzing sentiment in Twitter messages. You provide raw Twitter data, and it outputs an assessment of whether specific tweets are positive, negative, or neutral, and how people feel about particular topics or entities mentioned. This is ideal for anyone needing to gauge brand perception or public reaction on social media.
200 stars. No commits in the last 6 months.
Use this if you need to programmatically classify the sentiment of social media posts, either at the message level or concerning specific subjects mentioned within them.
Not ideal if you are looking for a ready-to-use application with a graphical interface for sentiment analysis, as this requires some programming setup.
Stars
200
Forks
64
Language
Python
License
MIT
Category
Last pushed
Jun 08, 2018
Commits (30d)
0
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