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CRAFT: A Crowd-Annotated Feedback Technique

 
: Hosseini, Mahmood; Groen, Eduard C.; Shahri, Alimohammad; Ali, Raian

:
Volltext urn:nbn:de:0011-n-4973087 (512 KByte PDF)
MD5 Fingerprint: 8cdc633efe03b2f4d7061fa5e6fa7e22
Erstellt am: 26.6.2018


Kaiserslautern, 2017, 6 S.
IESE-Report, 079.17/E
Reportnr.: 079.17/E
Englisch
Bericht, Elektronische Publikation
Fraunhofer IESE ()
crowdsourcing; requirements elicitation

Abstract
The ever increasing accessibility of the web for the crowd offered by various electronic devices such as smartphones has facilitated the communication of the needs, ideas, and wishes of millions of stakeholders. To cater for the scale of this input and reduce the overhead of manual elicitation methods, data mining and text mining techniques have been utilised to automatically capture and categorise this stream of feedback, which is also used, amongst other things, by stakeholders to communicate their requirements to software developers. Such techniques, however, fall short of identifying some of the seculiarities and idiosyncrasies of the natural language that people use colloquially. This paper proposes CRAFT, a technique that utilises the power of the crowd to support richer, more powerful text mining by enabling the crowd to categorise and annotate feedback through a context menu. This, in turn, helps requirements engineers to better identify user requirements within such feedback. This paper presents the theoretical foundations as well as the initial evaluation of this crowd-based feedback annotation technique for requirements identification.

: http://publica.fraunhofer.de/dokumente/N-497308.html