NLP-Create case real time based on negative sentiments (Text Analytics) identified in Tweets
As we know in this digital world where information plays a vital role in the growth of the business for any company. Companies promotional offers float around in social media to gain the customer’s attention.
Having said that companies has a bigger responsibility to care for their customer’s queries through various channels like Facebook, Twitter etc to improve on customer experience.
Question is how companies can handle millions of customers and respond to their customers queries real time as it is impossible to do it manually?
Here Text Analytics, Natural Language Prediction and Artificial Intelligence plays an important role to achieve this goal to analyze the customer query on social media by analyzing text sentiments and segregating the message in positive and negative sentiments and respond to those which needs attention.
I tried to put together one text analytics example where data is read from twitter and create the case into the Pega application for those tweets which need attention based on negative sentiments analyzed through artificial intelligence.
Hope this helps to the tech community to have a quick glance.
***Edited by Moderator: Lochan to tag as Developer knowledge share***
Hi Nikhil, nice article. I tried to follow this. But when I am trying to add create New Data set. Rule versions are not shown. Also Data-Social Twitter class is not shown as option. It exists in the application. However it is not shown in the available class list. Can someone help?