Detecting condolence, distress, and empathy in text
Project description
Condolence Models
Intro
condolence-models
is a package used to detect condolence and distress
expressions, as well as empathetic comments. It is released with the
EMNLP 2020 paper Condolence and Empathy in Online Commmunities
.
Install
Use pip
If pip
is installed, question-intimacy could be installed directly from it:
pip3 install condolence-models
Dependencies
python>=3.6.0
torch>=1.6.0
pytorch-transformers
markdown
beautifulsoup4
numpy
tqdm
simpletransformers
pandas
numpy
Usage and Example
See example.py
for an example of how to use the classifiers.
Note: The first time you run the code, the model parameters will need to be downloaded, which could take up significant space. The condolence and distress classifiers are about 500MB each, and the empathy classifier is about 1GB.
The interface for condolence and distress are the same. The interface for empathy is slightly different, to align with the simpletransformers interface more closely.
Classifying condolence or distress.
from condolence_models.condolence_classifier import CondolenceClassifier
cc = CondolenceClassifier()
# single string gets turned into a length-1 list
# outputs probabilities
print("I like ice cream")
print(cc.predict("I like ice cream"))
# [0.11919236]
# multiple strings
print(["I'm so sorry for your loss.", "F", "Tuesday is a good day of the week."])
print(cc.predict(["I'm so sorry for your loss.", "F", "Tuesday is a good day of the week."]))
# [0.9999901 0.8716224 0.20647633]
Classifying empathy.
from condolence_models.empathy_classifier import EmpathyClassifier
ec = EmpathyClassifier(use_cuda=True, cuda_device=2)
# list of lists
# first item is target, second is observer
# regression output on scale of 1 to 5
print([["", "Yes, but wouldn't that block the screen?"]])
print(ec.predict([["", "Yes, but wouldn't that block the screen?"]]))
# [1.098]
Contact
Naitian Zhou (naitian@umich.edu)
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for condolence_models-1.0.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4061a8c9fbe82e08531589ccd5fb304939952cd091bf99eabdb7a86be8934d19 |
|
MD5 | d21dadd3a4e0b69a3cf6a684af89ed11 |
|
BLAKE2b-256 | 2971fdcc7012191c6ce55a4a5a7a511d08dba038b8ec14ca42d259c551a2c910 |