Tonality & Sentiment Analysis


The language of incoming messages is detected automatically. Based on the result appropriate Natural Language Processing is applied to determine the tonality (sentiment) of each message. Besides other methods we apply Naïve Bayes classification and word vectors. The step of automatic text analysis is particularly adapted and optimized for the domain of financial markets. For example, the word “long” has a very unique (positive) meaning in the context of financial markets whereas it might mean something negative in a different context, e.g. if a user review in Amazon writes about a “long” focusing time of a digital camera.



StockPulse analyzes communication on financial topics in publicly accessible social media and news sources. Software evaluates hundreds of thousands of opinions and news articles every day and shows at a glance, how much and in what kind of mood people discuss about financial markets. Using latest Big Data technology, communication on stocks, indices, commodities, currency pairs and major market events is monitored and evaluated in real-time 24/7. Moreover, the software automatically generates buy and sell signals for different asset classes. By now, the database of StockPulse contains historical data of more than six years, enabling comprehensive backtestings. The software and trading models created by StockPulse were reviewed and confirmed by independent scientific studies.\n

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