Source code: https://github.com/draperunner/fjlc
This package is a Python port of the Lexicon Creator and Classifier of Valerij Fredriksen and Brage Ekroll Jahren (2016). It is compatible with Python version >= 3.
The original Java code is available here: https://github.com/freva/Masteroppgave
If using this package in your publications, please cite
Valerij Fredriksen and Brage Ekroll Jahren. Twitter Sentiment Analysis: Exploring Automatic Creation of Sentiment Lexica. Master's thesis, 2016.
pip install fjlc
The LexiconClassifier
uses the best performing lexicon of Fredriksen and Jahren. You can specify your own lexicon, see Options below.
from fjlc import LexiconClassifier
lc = LexiconClassifier()
You can classify a single tweet or a list of tweets:
lc.classify("I am happy!") # 'POSITIVE'
lc.classify(["I am happy!", "I hate rain"]) # ['POSITIVE', 'NEGATIVE']
You can get the sentiment value of a single tweet or multiple tweets
lc.calculate_sentiment("I am happy!") # 5.599244615570646
lc.calculate_sentiment(["I am happy!", "I hate rain"]) # [5.599244615570646, -2.767224666516315]
The LexiconClassifier
takes three options:
lexicon
: Path to sentiment lexicon fileoptions
: Path to options filedictionary
: Path to canonical dictionary
from fjlc import LexiconCreator
lc = LexiconCreator()
Incomplete, untested.