Metadata-Version: 2.1
Name: crowdtruth
Version: 2.1
Summary: Disagreement based metrics for the processing and evaluation of crowdsourced annotations
Home-page: http://crowdtruth.org
Author: Vrije Universiteit Amsterdam
Author-email: crowdwatson@gmail.com
License: Apache 2.0
Download-URL: https://github.com/CrowdTruth/CrowdTruth-core/archive/2.1.zip
Keywords: CrowdTruth,crowdsourcing,disagreement,metrics,crowdflower,amazon mechanical turk
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Human Machine Interfaces
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Linguistic
Requires-Dist: pymodm (>=0.3.0)
Requires-Dist: pandas (>=0.23.1)
Requires-Dist: numpy (>=1.13.3)
Requires-Dist: scipy (>=1.0.0)
Requires-Dist: chardet (>=3.0.4)
Requires-Dist: coverage (>=4.5.1)
Requires-Dist: codecov (>=2.0.15)
Requires-Dist: dateparser (>=0.7.0)

CrowdTruth is an approach to machine-human computing for collecting annotation data on text, images and videos. The approach is focussed specifically on collecting annotation data by capturing and interpreting inter-annotator disagreement.