Textual Affect Sensing for Sociable and Expressive Online Communication
Textual Affect Sensing for Sociable and Expressive Online Communication
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DOI：
10.1007/978-3-540-74889-2_20
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发表时间：
2007-09
期刊：
影响因子：
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通讯作者：
Alena Neviarouskaya;H. Prendinger;M. Ishizuka
中科院分区：
文献类型：
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作者：
Alena Neviarouskaya;H. Prendinger;M. Ishizuka
在本文中，我们解决了识别和解释的影响，通过短信沟通的任务。在线会话中语言的演变性质是这种媒体类型的影响感知的主要问题，因为句子解析可能会失败，而句法结构分析。开发的情感分析模型的目的是处理不仅正确的书面文本，但也写在缩写或表达方式的非正式消息。所提出的基于规则的方法处理每个句子的顺序阶段，包括符号线索处理，检测和转换的缩写，句子解析，单词/短语/句子级分析。在一项基于160个句子的研究中，在70%的情况下，系统结果与三分之二的人类注释者一致。为了反映检测到的情感信息和社交行为，创建了化身。
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.