Linguistic Analysis of Crowd Requirements: An Experimental Study
Javed Ali Khan, Lin Liu, Yidi Jia, Lijie Wen · 2018
Users of today's online software services are often diversified and distributed, whose needs are hard to elicit using conventional RE approaches. As a consequence, crowd-based, data intensive requirements engineering approaches are considered important. In this paper, we have conducted an experimental study on a dataset of 2,966 requirements statements to evaluate the performance of three text clustering algorithms. The purpose of the study is to aggregate similar requirement statements suggested by the crowd users, and also to identify domain objects and operations, as well as required features from the given requirements statements dataset. The experimental results are then cross-checked with original tags provided by data providers for validation.