python-webis: Python wrapper for the webis Twitter sentiment evaluation ensemble

Research output: Non-textual formSoftwareScientific

Abstract

This is a Python wrapper around the Java implementation of a Twitter sentiment evaluation framework presented by Hagen et al. (2015). In Zimbra et al. (2018)’s evaluation of “The State-of-the-Art in Twitter Sentiment Analysis” this approach received the highest score in classification accuracy (average across five categories of content, table 4, p5:15).

This package is available from the PyPi software repository: https://pypi.org/project/webis/
Its source code is hosted on GitLab: https://gitlab.com/christoph.fink/python-webis
Original languageEnglish
Media of outputinternet
Size40kB
DOIs
Publication statusPublished - 23 Jan 2019
MoE publication typeI2 ICT software

Fields of Science

  • 1172 Environmental sciences
  • 6160 Other humanities

Cite this

@misc{3b2689061d3e4171b2fc5a07171d2314,
title = "python-webis: Python wrapper for the webis Twitter sentiment evaluation ensemble",
abstract = "This is a Python wrapper around the Java implementation of a Twitter sentiment evaluation framework presented by Hagen et al. (2015). In Zimbra et al. (2018)’s evaluation of “The State-of-the-Art in Twitter Sentiment Analysis” this approach received the highest score in classification accuracy (average across five categories of content, table 4, p5:15).This package is available from the PyPi software repository: https://pypi.org/project/webis/ Its source code is hosted on GitLab: https://gitlab.com/christoph.fink/python-webis",
keywords = "1172 Environmental sciences, 6160 Other humanities",
author = "Fink, {Christoph Alexander}",
year = "2019",
month = "1",
day = "23",
doi = "10.5281/zenodo.2547461",
language = "English",

}

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AU - Fink, Christoph Alexander

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Y1 - 2019/1/23

N2 - This is a Python wrapper around the Java implementation of a Twitter sentiment evaluation framework presented by Hagen et al. (2015). In Zimbra et al. (2018)’s evaluation of “The State-of-the-Art in Twitter Sentiment Analysis” this approach received the highest score in classification accuracy (average across five categories of content, table 4, p5:15).This package is available from the PyPi software repository: https://pypi.org/project/webis/ Its source code is hosted on GitLab: https://gitlab.com/christoph.fink/python-webis

AB - This is a Python wrapper around the Java implementation of a Twitter sentiment evaluation framework presented by Hagen et al. (2015). In Zimbra et al. (2018)’s evaluation of “The State-of-the-Art in Twitter Sentiment Analysis” this approach received the highest score in classification accuracy (average across five categories of content, table 4, p5:15).This package is available from the PyPi software repository: https://pypi.org/project/webis/ Its source code is hosted on GitLab: https://gitlab.com/christoph.fink/python-webis

KW - 1172 Environmental sciences

KW - 6160 Other humanities

UR - https://gitlab.com/christoph.fink/python-webis

UR - https://pypi.org/project/webis/#description

U2 - 10.5281/zenodo.2547461

DO - 10.5281/zenodo.2547461

M3 - Software

ER -