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首页> 外文会议>International workshop on enterprise applications and services in the finance industry >A Proposed Framework for Evaluating the Effectiveness of Financial News Sentiment Scoring Datasets
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A Proposed Framework for Evaluating the Effectiveness of Financial News Sentiment Scoring Datasets

机译：拟议框架，用于评估财务新闻情绪评分数据集的有效性

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摘要

The impact of financial news on financial markets has been studied extensively. A number of news sentiment scoring techniques are being widely used in research and industry. However, results from sentiment studies are hard to interpret contextual and sentiment related parameters change. Sometimes, the conditions which lead to the results are not fully documented and the results are not repeatable. Based on service-oriented computing principles, this paper proposes a framework that automates the process of incorporating different contextual parameters when running news sentiment impact studies. The framework also preserves the set of parameters/dataset and conditions for the end user to enable them to reproduce their results. This is demonstrated using a case study that shows how end users can flexibly select different contextual and sentiment related parameters and conduct news impact studies on daily stock prices.
机译：广泛研究了财务新闻对金融市场的影响。许多新闻情绪评分技术正在广泛应用于研究和行业。然而，情绪研究的结果很难解释语境和情绪相关参数的变化。有时，导致结果导致结果的条件没有完全记录，结果不可重复。本文基于面向服务的计算原则，提出了一种框架，可以在运行新闻情绪影响研究时自动化结合不同的上下文参数的过程。该框架还保留了最终用户的参数/数据集和条件，使其能够重现它们的结果。使用案例研究证明了，显示最终用户如何灵活地选择不同的上下文和情绪相关参数，并对日常股票价格进行新闻影响研究。

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