A detailed step-by-step description of the design of a software system, this paper gives the reader an idea about the functioning of a knowledge-driven application.

The purpose of the reported research is to show and advertise a toolkit that allows the analysis of tweet streams in real time. The solution is based on the general architecture for text engineering (GATE) platform and extended with a tweet-harvesting application programming interface (API) in real time with good performance. The paper reads like a report of project work. Special attention is paid to explaining the effects of the adopted semantic web and linked data technologies approach in the effectiveness of the solution.

The framework has been tested on several use cases, which are described in the paper. These use cases, more precisely application domains, are measuring climate change engagement; analysis of Brexit tweets, including analysis of voting trends; and a hashtag predictor. Although the paper discusses issues about opinion mining and sentiment analysis, it does not provide an explanation of the improvements and the contribution of the reported research. The authors show queries and examples of visualizations of results.

A very easy-to-read report of the integration of software components into a working framework with universal domain-independent coverage, this paper is a good read for practitioners interested in adopting an off-the-shelf solution that allows one to harvest insight from Twitter in real-time on an arbitrarily selected topic.