TY - GEN
T1 - CRAFT
T2 - 25th IEEE International Requirements Engineering Conference Workshops, REW 2017
AU - Hosseini, Mahmood
AU - Groen, Eduard C.
AU - Shahri, Alimohammad
AU - Ali, Raian
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/29
Y1 - 2017/9/29
N2 - 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 peculiarities 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.
AB - 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 peculiarities 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.
KW - Crowdsourced text mining
KW - Crowdsourcing
KW - Feedback categorisation
KW - Requirements elicitation
UR - https://www.scopus.com/pages/publications/85034624394
U2 - 10.1109/REW.2017.27
DO - 10.1109/REW.2017.27
M3 - Conference contribution
AN - SCOPUS:85034624394
T3 - Proceedings - 2017 IEEE 25th International Requirements Engineering Conference Workshops, REW 2017
SP - 170
EP - 175
BT - Proceedings - 2017 IEEE 25th International Requirements Engineering Conference Workshops, REW 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 September 2017 through 8 September 2017
ER -