ML-Ask: Open Source Affect Analysis Software for Textual Input in Japanese

We present ML-Ask - the first Open Source Affect Analysis system for textual input in Japanese. ML-Ask analyses the contents of an input (e.g., a sentence) and annotates it with information regarding the contained general emotive expressions, specific emotional words, valence-activation dimensions o...

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Bibliographic Details
Published in:Journal of Open Research Software 2017, Vol.5
Main Authors: Ptaszynski, Michal, Dybala, Pawel, Rzepka, Rafal, Araki, Kenji, Masui, Fumito
Format: Report
Language:English
Subjects:
Japanese language
Open source software
Technology application
Translation (Languages)
Online Access:Get full text
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Description
Summary:We present ML-Ask - the first Open Source Affect Analysis system for textual input in Japanese. ML-Ask analyses the contents of an input (e.g., a sentence) and annotates it with information regarding the contained general emotive expressions, specific emotional words, valence-activation dimensions of overall expressed affect, and particular emotion types expressed with their respective expressions. ML-Ask also incorporates the Contextual Valence Shifters model for handling negation in sentences to deal with grammatically expressible shifts in the conveyed valence. The system, designed to work mainly under Linux and MacOS, can be used for research on, or applying the techniques of Affect Analysis within the framework Japanese language. It can also be used as an experimental baseline for specific research in Affect Analysis, and as a practical tool for written contents annotation.
ISSN:2049-9647
2049-9647
DOI:10.5334/jors.149