Studying Attention Models in Sentiment Attitude Extraction Task

UPD December 18'th, 2020: Fixed bug in results evaluation; the latter might affect on prec/recall for documents that lacks of neutral opinions in model results. [issue #1]

UPD May 28'th, 2020: An additional restriction towards entity pairs considered as an attitude in context. We treat pairs between object and subject appeared in context only when the distance between them in words (terms) not greater than 10. [source code reference] (this feature was commented)

Figure: Weight distribution visualization for model Att-BLSTM on sentiment contexts, where attitude is conveyed by frame (colored), presented in context.

This repository provides a source code of models and related experiments, conducted as a part of the following paper:

• Studying Attention Models in Sentiment Attitude Extraction Task [Springer] / [arXiv:2006.11605] / [presentaiton]
  • Rusnachenko Nicolay, Loukachevitch Natalia
  • NLDB-2020

Dependencies

• Python-2.7
• arekit-0.20.0-nldb-rc

Installation

• Core library installation: All the implementation depends on core library for sentiment attitude extraction, dubbed as arekit-0.20.0:

NOTE: it is important to download in arekit directory.

# Download arekit-0.20.0
git clone --single-branch --branch 0.20.0-nldb-rc https://github.com/nicolay-r/AREkit arekit

# Install dependencies
pip install -r arekit/dependencies.txt

• Resources: Since arekit-0.20.0 all the resources such as collections (RuAttitudes, RuSentRel) and lexicons (RuSentiLex) are a part o``f the related library.

• Word2Vec: installation assumes to run a download.sh script:

cd data && ./download.sh

References

@inproceedings{rusnachenko-2020-attention,
    title = "Studying Attention Models in Sentiment Attitude Extraction Task",
    author = "Rusnachenko, Nicolay  and Loukachevitch, Natalia",
    journal = "M\'etais E., Meziane F., Horacek H., Cimiano P. (eds) Natural Language Processing and Information Systems. 
        NLDB 2020. Lecture Notes in Computer Science, vol 12089. Springer, Cham",
    booktitle = "Proceedings of the 25th International Conference on Natural Language and Information Systems",
    year = "2020",
    url = "https://doi.org/10.1007/978-3-030-51310-8_15",
    doi = "10.1007/978-3-030-51310-8_15",
}