Stylized Facts of Linguistic Corpora: Exploring the Lexical Properties of Affect in News

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• 关键词：Text analysis ; Corpus linguistics ; Linguistic properties ; Stylized facts ; Sentiment analysis
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9937
• 期：1
• 页码：494-502
• 全文大小：153 KB
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• 作者单位：Jason A. Cook (21)
  Zeyan Zhao (21)
  Khurshid Ahmad (21)
  
  21. School of Computer Science and Statistics, Trinity College, Dublin, Ireland
  
• 丛书名：Intelligent Data Engineering and Automated Learning ¨C IDEAL 2016
• ISBN：978-3-319-46257-8
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9937

文摘

Investors are often said to be driven by emotions, and studies in sentiment analysis claim that there is a causal relationship between negative affect in text and prices in financial markets. The text collections used in these studies tend to be of varying sizes and sources, with little justification of their design criteria. This is a classic data engineering problem, which requires specification of the data sources and design of the data repositories and retrieval facilities. In this paper, we explore the statistical properties of negative affect expressed in various textual corpora, differing in specification, size and provenance. The question we ask is whether there are any stylized facts of negative affect that are universal across all texts. We observed two main findings: (1) The frequency distribution of negative terms is generally stable across different corpus sizes and (2) The frequency of negative terms accounts for a relatively small proportion of the total terms in the corpus.