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Textual Affect Sensing for Sociable and Expressive Online Communication

TitleTextual Affect Sensing for Sociable and Expressive Online Communication
Publication TypeBook Chapter
Year of Publication2007
AuthorsNeviarouskaya, A, Prendinger, H, Ishizuka, M
EditorPaiva, A, Prada, R, Picard, R
Book TitleAffective Computing and Intelligent Interaction
Series TitleLecture Notes in Computer Science
Volume4738
Pagination218-229
PublisherSpringer
CityBerlin / Heidelberg
ISBN978-3-540-74888-5
Abstract

In this paper, we address the tasks of recognition and interpretation of affect communicated through text messaging. The evolving nature of language in online conversations is a main issue in affect sensing from this media type, since sentence parsing might fail while syntactical structure analysis. The developed Affect Analysis Model was designed to handle not only correctly written text, but also informal messages written in abbreviated or expressive manner. The proposed rule-based approach processes each sentence in sequential stages, including symbolic cue processing, detection and transformation of abbreviations, sentence parsing, and word/phrase/sentence-level analyses. In a study based on 160 sentences, the system result agrees with at least two out of three human annotators in 70% of the cases. In order to reflect the detected affective information and social behaviour, an avatar was created.

URLhttp://research.nii.ac.jp/~prendinger/papers/ACII2007-Neviarouskaya.pdf
DOI10.1007/978-3-540-74889-2_20