Sentiment Classification and NLP Analysis
Our platform classifies sentiment of millions of social media posts and other texts per day, using machine learning (Support Vector Machines). Sentiment analysis is provided in real-time and can be combined with Named Entity Recognition to determine sentiment on level of individual entities. Entitites can be stocks, blockchain assets, bank products, etc. Platform uses powerful NLP algorithms (Latent Dirichlet Allocation and others) to extract main topics discussed in texts.
Use cases - stocks, blockchain assets, chats, phone conversations, emails
Our solution can be adapted to various needs, we use it for our BittsAnalytics platform for analysis of blockchain assets and stocks. In financial institutions it can be applied to determine topics and sentiment of customer interactions, analysing chats, emails and even phone conversations. For the latter we can provide you with speech recognition solution to transcribe phone conversations in texts. Our sentiment classification and NLP analysis platform provides financial institutions a real-time view of customer interactions in terms of sentiment and topics discussed.