Expert.ai Announces Winners of Sentiment & Opinion Mining Hackathon

The three winning projects and category winners demonstrated the ease with which customer support can be enhanced with advanced natural language- (NL) based analytics

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.

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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 and powerful 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, etc.

Fifty-seven projects were submitted to the expert.ai 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 prize 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.

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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. The category prize winners are;

• Echodex (Identifying Sentiment of Brands, Companies, or Products category) is a web application that aggregates data from multiple sources (news websites, reddit, twitter), and uses NLP tools from expert.ai to show structured analysis on the content retrieved;
• StOnKs (Identifying Sentiment of Events, Policies, or Products category), performs sentiment analysis, powered by expert.ai, on comments extracted from the Reddit forum, r/WallStreetBet to better understand equity pricing patterns in the market;
• Sidr Gmail Support Assistant (Using Customer Interaction Analytics to Solve Customer Support Challenges category), is a support assistant that extracts insights from support emails, providing email categories, key phrases and sentiment based on advanced expert.ai NL features.

“We were very impressed and excited by the projects in our Sentiment & Opinion Mining Natural Language API Hackathon,” said Brian Munz, Product Manager, NL API & Developer Experience at expert.ai. “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.”

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