Concept-Level Sentiment Analytics
1. OUR SOLUTIONSUsers do not need to change their OS, UI or IDE: our APIs are easy to use and to embed in any framework. Our company offer fine-grained solutions to many subtasks of sentiment analysis, e.g., polarity detection, aspect extraction, subjectivity detection, temporal tagging, named-entity recognition, concept extraction, personality recognition, and sarcasm detection, and they are available in different domains, modalities, and languages. 2. OUR TRANSPARENCYWe show you what data is collected and how each of them is classified. Most companies, instead, adopt a black-box strategy in which they only show you the classification results. This way users can never be sure about how accurate their analysis really is because they usually do not disclose neither the data nor the techniques adopted for classifying such data (which, in most cases, are rather obsolete). 3. OUR APPROACHNLP research is evolving very fast, and the only way to be up-to-date with it is to be fully immersed in academia. We are not just a business company but also a research lab. We know the current and future trends of NLP, and we always embed the latest techniques in our APIs. Unlike most companies (which tend to focus only on one facet of the problem), we take a very multidisciplinary approach to sentiment analysis.