Python Machine Learning based API to predict sentiment for Persian text.
Project description
Persian Sentiment Analysis
A trained model to predict sentiment class of a given Persian text.
Installation
pip3 install persian_sa
Read More:
To find about preprocessing and feature engineering, and how the model predicts visit arXiv.
Usage:
Running the source code
- To run the program, use python3 persian_sa.py
- Next you will be prompted to give a Persian text as input.
- To exit the program write
exiton terminal.
MOHAMMADs:persian_sa mohammadkasra$ python3 persian_sa.py
This app uses ML to predict setntiment (e.g., Positive or Negative)
of a given Persian text. Toexit the app write 'exit' in terminal.
Input: زیاد در خاطرات دیگران ورود نکنید، چرا که در خاطرات هر شخص رازهایی وجود دارد که حتی می ترسد آن ها را برای خودش آشکار کند!
... Negative!
Input: زندگی همچون یک آینه است زمانی که در آن لبخند بزنیم شگفت انگیزترین نتایج را به دست خواهیم آورد
... Positive!
Input: exit
... exit: 0
MOHAMMADs:persian_sa mohammadkasra$
Running with after Pip install
>>> from persian_sa.persian_sa import persian_sa
>>>
>>> persian_sa.predict_sentiment('می تواند به همین دلیل از آن متنفر باشد')
'Negative!'
>>> # Or you can predict the class number; if you set "return_class_label = True"
>>> persian_sa.predict_sentiment('می تواند به همین دلیل از آن متنفر باشد', return_class_label = True)
0
>>> persian_sa.predict_sentiment('اجرای آنها شادی مطلق است')
'Positive!'
>>> persian_sa.predict_sentiment('اجرای آنها شادی مطلق است', return_class_label = True)
1
>>>
CHANGE LOG:
++++++++++++++++++++++CHANGE LOG+++++++++++++++++++++ +++++++++++++++++++++++++++++++++++++++++++++++++++++
..... Version 0.2.3 --> 26.01.2021 --> 1st Release | | | | | | | | | .....................................................
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