Increasing attention has been drawn to the sentiment analysis of financial documents. The most popular examples of such documents include analyst reports and economic news, the analysis of which is frequently used to capture the trends in market sentiments. On the other hand, the significance of the role sentiment analysis plays in the financial domain has given rise to the efforts to construct a financial domain-specific sentiment lexicon. Sentiment lexicons lend a hand for solving various text mining tasks, such as unsupervised classification of text data, while alleviating the arduous human labor required for manual labeling. One of the challenges in the construction of an effective sentiment lexicon is that the semantic orientation of a word may change depending on the context in which it appears. For instance, the word ``profit" usually conveys positive sentiments; however, when the word is juxtaposed with another word ``decrease," the sentiment associated with the phrase ``profit decreases" now becomes negative. Hence, the sentiment of a given word may shift as one begins to consider the context surrounding the word. In this paper, we address this issue by incorporating context when building sentiment lexicon from a given corpus. Specifically, we construct a lexicon named Senti-DD for the Sentiment lexicon composed of Direction-Dependent words, which expresses each term a pair of a directional word and a direction-dependent word. Experiment results show that higher classification performance is achieved with Senti-DD, proving the effectiveness of our method for automatically constructing a context-aware sentiment lexicon in the financial domain.

中文翻译：

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使用方向相关词自动构建金融领域上下文感知情感词典

对财务文件的情感分析越来越受到关注。此类文件最受欢迎的例子包括分析师报告和经济新闻，其分析经常用于捕捉市场情绪的趋势。另一方面，情感分析在金融领域所起的重要作用促使人们努力构建金融领域特定的情感词典。情感词典有助于解决各种文本挖掘任务，例如文本数据的无监督分类，同时减轻手动标记所需的繁重人力。构建有效情感词典的挑战之一是，单词的语义方向可能会根据它出现的上下文而改变。例如，“利润”这个词 通常传达积极的情绪；然而，当这个词与另一个词“减少”并列时，与短语“利润减少”相关的情绪现在变得消极。因此，当人们开始考虑围绕该词的上下文时，给定词的情绪可能会发生变化。在本文中，我们通过在从给定语料库构建情感词典时结合上下文来解决这个问题。具体来说，我们为由方向依赖词组成的情感词典构建了一个名为 Senti-DD 的词典，它表示每个术语一对方向词和一个方向依赖词。实验结果表明，Senti-DD 实现了更高的分类性能，证明了我们的方法在金融领域自动构建上下文感知情感词典的有效性。