HeartBeat

Tengri Wallet
Used:
Python Django PostgreSQL ReactJS

Client:

HeartBeat (Canada)

Task:

To design a tool to analyze survey results for emotional mapping. The technology would allow adding words and referring them to particular emotional groups as well as maintaining a user-friendly interface for reports compilation and visualization of survey results analysis.

There are many implicit objective tools for gauging emotions. Although feelings are personal and subjective, human brain turns them into a standard code which renders emotions through various feelings, situations, and even people. The segmentation of emotions was developed based on the classification of emotions by W. Gerrod Parrott of Georgetown University and was implemented in the product. The system helps companies to do a precise thorough analysis of emotional factors of behavior and to understand their employees, clients, and patients better.

Outcome:

The developed application allows for uploading data and obtaining various reports in a form of graphs and tables. To understand and analyze emotions, Heartbeat processes language (unstructured text) that people use to describe their conscious feelings. The algorithm takes this textual data and converts it into a binary code that represents primary and secondary emotions.

Intellectual text analytics Heartbeat is based on comprehensive taxonomy, a science of classification, of over 20,000 multigrams, or emotional words and phrases, professionally encoded into 100 secondary categories. Each word and phrase represent one or several secondary emotional categories.

At the moment the development of the product is ongoing.

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