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Recognizing Emotional Content of Emails as a byproduct of Natural Language Processing-based Metadata Extraction

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2006, v.23 no.2, pp.167-183
https://doi.org/10.3743/KOSIM.2006.23.2.167

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Abstract

This paper describes a metadata extraction technique based on natural language processing (NLP) which extracts personalized information from email communications between financial analysts and their clients. Personalized means connecting users with content in a personally meaningful way to create, grow, and retain online relationships. Personalization often results in the creation of user profiles that store individuals preferences regarding goods or services offered by various e-commerce merchants. We developed an automatic metadata extraction system designed to process textual data such as emails, discussion group postings, or chat group transcriptions. The focus of this paper is the recognition of emotional contents such as mood and urgency, which are embedded in the business communications, as metadata.

keywords
Information Extraction, Metadata, Emotional Content, 메타데이터, 정보추출, 감성정보, 자연어처리, Information Extraction, Metadata, Emotional Content

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Journal of the Korean Society for Information Management