Sentiment analysis has applications in diverse contexts such as in the gathering and
analysis of opinions of individuals about various products, issues, social, and political …

There is growing evidence that the classical notion of adversarial robustness originally
introduced for images has been adopted as a de facto standard by a large part of the NLP …

The marvel of markets lies in the fact that dispersed information is instantaneously
processed and used to adjust the price of goods, services and assets. Financial markets are …

Finance-related news such as Bloomberg News, CNN Business and Forbes are valuable
sources of real data for market screening systems. In news, an expert shares opinions …

Companies listed on the stock markets are typically obliged to publicly disclose any
information that might have a significant influence on their stock prices. This transparency …

Decision support for financial news using natural language processing requires robust
methods that process all sentences correctly, including those that are negated. To predict …

We present the results of an evaluation study in the context of lexicon-based sentiment
analysis resources for German texts. We have set up a comprehensive compilation of 19 …

This paper aims to operationalize subjective information processing in financial news
disclosures. In order to measure news tone, previous research commonly utilizes manually …

Online opinionated data has increased tremendously since the arrival of web 2.0. Users
have the authority to generate online content expressing their sentiments or opinions …

Textual materials represent a rich source of information for improving the decision-making of
people, businesses and organizations. However, for natural language processing (NLP), it is …