Extracting Sentiment Attitudes From Analytical Texts

Natalia Loukachevitch, Nicolay Rusnachenko

8/27/2018

cs.CL

Official code: nicolay-r/RuSentRel (9 stars, MIT, last commit 2023-10-01).

Abstract

In this paper we present the RuSentRel corpus including analytical texts in the sphere of international relations. For each document we annotated sentiments from the author to mentioned named entities, and sentiments of relations between mentioned entities. In the current experiments, we considered the problem of extracting sentiment relations between entities for the whole documents as a three-class machine learning task. We experimented with conventional machine-learning methods (Naive Bayes, SVM, Random Forest).

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Code Implementations(1)

nicolay-r/RuSentRelOfficial100%

MIT

Dataset as a part of DIALOG'2018 paper: "Extracting Sentiment Attitudes From Analytical Texts"

92PythonApr 10, 20183 years agoMIT

attitude-determinationdataset

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Cite this paper

@article{loukachevitch2018extracting,
  title  = {Extracting Sentiment Attitudes From Analytical Texts},
  author = {Natalia Loukachevitch and Nicolay Rusnachenko},
  year   = {2018},
  eprint = {1808.08932},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1808.08932}
}

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