Python wrapper for the webis Twitter sentiment identification tool
Project description
Python wrapper for the webis Twitter sentiment evaluation ensemble
This is a Python wrapper around the Java implementation of a Twitter sentiment evaluation framework presented by Hagen et al. (2015). The example script fetches Tweets from a PostgreSQL database, uses PyJnius to call the Java modules to evaluate the sentiment, and saves results to a table in the same database.
Dependencies
The script is written in Python 3 and depends on the Python modules PyJnius, pandas and emojientities.
On top of that, a Java Runtime Environment (jre) is required, plus a matching Java Development Kit (jdk). We used Java 8, but other versions might work just as well. OpenJDK works fine.
To install all dependencies on a Debian-based system, run:
apt-get update -y &&
apt-get install -y python3-dev python3-pip python3-virtualenv cython3 openjdk-8-jdk-headless openjdk-8-jre-headless ca-certificates-java
Installation
- using
pip
or similar:
pip3 install webis
-
OR: manually:
- Clone this repository
git clone https://gitlab.com/christoph.fink/python-webis.git
- Change to the cloned directory
- Use the Python
setuptools
to install the package:
cd python-webis python3 ./setup.py install
-
OR: (Arch Linux only) from AUR:
# e.g. using yaourt
yaourt python-webis
Usage
Import the webis
module. On first run, python-webis will download and compile the Java backend – this might take a few minutes.
Then instantiate a webis.SentimentIdentifier
object and use its identifySentiment()
function, passing in a list of tuples ([(tweetId, tweetText),(tweetId, tweetText), … ]
), a dict ({tweetId: tweetText, … }
) or a pandas.DataFrame
(first column is treated as identifier, second as tweetText).
The function returns a list of tuples ([(tweetId, sentiment), … ]
), a dict ({tweetId: sentiment, … }
) or a data frame (first column id, second column sentiment) of rows it successfully identified a sentiment of. The type of the return value matches the argument, with which the function is called. The tweetId
values will be cast to the type of the first row’s tweetId
.
import webis
sentimentIdentifier = webis.SentimentIdentifier()
tweets = [
(1, "What a beautiful morning! There’s nothing better than cycling to work on a sunny day 🚲."),
(2, "Argh, I hate it when you find seven (7!) cars blocking the bike lane on a five-mile commute")
]
sentimentIdentifier.identifySentiment(tweets)
# [(1, "positive"), (2, "negative")]
import pandas
tweets = pandas.DataFrame(tweets)
sentimentIdentifier.identifySentiment(tweets)
# sentiment tweetId
# 0 positive 1
# 1 negative 2
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