Expert.ai announced today the winners of the "Sentiment & Opinion Mining Natural Language API" Hackathon. From May 6 to June 22, hundreds of developers across the globe unleashed their creativity to develop or enhance existing apps by using the expert.ai NL API to identify emotions and traits within documents, chat messages, and emails as well as ascertain the overall sentiment of the text.
Given that more than 80% of business data is unstructured and expressed in the form of language, accelerating time-to-value of more intelligent NL-aware apps is a business imperative. The expert.ai NL API offers a simple way to address even the most complex unstructured data management use cases, including the ability to monitor reactions on social media, improve routing of customer support by capturing emotions, and behavioral traits as well as to extract the general sentiment towards brands, events, policies, products, and so forth.
Fifty-seven projects were submitted to the hackathon for a chance to win a total of $10,000 in prizes, and each project was judged on their creativity, the number of API features included in the project, and the overall impact or potential value the project could provide to users. First, second, and third prizes were awarded to apps designed to augment user experiences by leveraging the natural language capabilities of the expert.ai NL API to extract a deeper understanding of text.
First place went to Smart Voicenotes by EveryWord, an app that provides text versions of WhatsApp voice notes and a detailed summary of the key aspects, including sentiment analysis, key-phrase detection, and named entity recognition features from expert.ai, without ever leaving the WhatsApp user interface.
Second place was awarded to Clyde Chrome Extension, a Chrome extension that brings advanced natural language processing and opinion mining capabilities directly to a user's browser.
Third place went to Multilingual Sentiment Analyzer which leverages the expert.ai NL API functionalities together with tooling for information retrieval and machine translation to make sure user feedback collections are easily searchable and can be filtered at a fine-grained level before they are processed by the expert.ai sentiment module.
The hackathon also offered three category prizes to recognize the best project identifying sentiment of brands, companies, or products, the best project identifying sentiment of events, policies, or products, and the best project using customer interaction analytics to solve customer support challenges.
"We were very impressed and excited by the projects in our Sentiment & Opinion Mining Natural Language API Hackathon," said expert.ai Product Manager, NL API & Developer Experience Brian Munz.
"The creativity and variety of use cases featured by the developers highlighted the power and opportunity of NLP in real-world web applications. The success of these talented developers validated our belief that our NL API is set to be a trailblazing technology that makes it easy to add powerful natural language capabilities into a web application. We can't wait to see what comes next," said Munz.