A lot of customers are turning to social media and networking channels such as Twitter, Facebook, LinkedIn, YouTube, blogs, and discussion forums to provide feedback on different products and services. It is, therefore, vital that businesses collate, consolidated, and analyze this data. The trouble with that is that often it is too much information to track it or follow it manually.
Marlabs’ social sentiment interpreter tool SocialSenser provides a comprehensive and dynamic framework for measuring and monitoring customer feedback from social media. The tool analyzes sentiments in comments using dynamic and customizable semantic algorithm, and also provides demographic analysis of users in certain social media. It uses updated Java libraries, OpenNLP tools, SQL databases, and advanced visualization tools using comprehensive programming and configuration models. Here are some of its features: