Customer Requirements Elicitation based on Social Network Service

Lee, Yoon-kyu

doi:10.3837/tiis.2011.10.003

Cited by 9 publications

(9 citation statements)

References 8 publications

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“…Lee et al 33 presented an SNS‐based requirements elicitation technique that has four phases. (1) The preparation phase in which the domain‐related keywords are selected according to their popularity.…”

Section: Resultsmentioning

confidence: 99%

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Social network sites and requirements engineering: A systematic literature review

Ali

Hong

Chung

2020

J Software Evolu Process

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A large volume of highly diverse and real‐time data provided by social network sites has revolutionized several data analytical sciences such as stock exchange fluctuation prediction, sentiment analysis, and political affiliations prediction. From a software engineering viewpoint, social network sites have produced an unprecedented opportunity for software development organizations to monitor the opinion of the large population of users of their systems. The extracted data from social network sites can be used to extract information about newly launched systems, and it enable software development organizations to obtain rapid technical and social feedback about their systems. This paper presents on a systematic literature review of the published research articles on how requirements engineering (RE) activities are conducted using social network sites, elaborated in studies published between 2011 and 2019. From the resulting studies, we extracted data to answer our four questions related to social network site (SNS)‐based RE approaches focusing on requirements elicitation, prioritization, and negotiation activities. Thirty‐one relevant studies were identified and analyzed to answer our research questions. Among 31 studies, 62% of the studies reportedly support requirements elicitation activity, and 14% of the studies reportedly support requirements elicitation, prioritization, and negotiation activities. Ten percent studies were about requirements elicitation and prioritization activities, 7% of the studies support both requirements elicitation and negotiation activities, and prioritization activity was supported by 7% of the studies. It was also observed that 58% of the selected studies adopted semi‐automatic approaches to conduct RE activities while 21% of the selected studies proposed automatic tools, and 21% of the selected studies adopted manual approaches to conduct RE activities. The outcomes of this systematic literature review indicate that social network sites can be a major source that can be used successfully to extract and identify user requirements. Moreover, this systematic literature review also presents implications of this study for practitioners and researchers including challenges, unresolved issues, and future research directions.

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Section: Resultsmentioning

confidence: 99%

“…Lee et al 33 Guzman et al 34 employed Twitter to elicit user requirements to evolve software systems. The authors presented the ALERTme approach, which includes tweet dataset, preprocessing, classification, grouping, and ranking of tweets.…”

Section: Resultsmentioning

confidence: 99%

Social network sites and requirements engineering: A systematic literature review

Ali

Hong

Chung

2020

J Software Evolu Process

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“…It enables engineers to elicit data from Twitter and analyze it using NLP techniques to find potential requirements. Twitter was selected because it is a popular microblogging social-media network and a potential data source to extract requirements [30,31].…”

Section: Proposed Continuous Requirements-elicitation Methodologymentioning

confidence: 99%

Crowd-Generated Data Mining for Continuous Requirements Elicitation

Alwadain¹,

Alshargi²

2019

IJACSA

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In software development projects, the process of requirements engineering (RE) is one in which requirements are elicited, analyzed, documented, and managed. Requirements are traditionally collected using manual approaches, including interviews, surveys, and workshops. Employing traditional RE methods to engage a large base of users has always been a challenge, especially when the process involves users beyond the organization's reach. Furthermore, emerging software paradigms, such as mobile computing, social networks, and cloud computing, require better automated or semi-automated approaches for requirements elicitation because of the growth in systems users, the accessibility to crowd-generated data, and the rapid change of users' requirements. This research proposes a methodology to capture and analyze crowd-generated data (e.g., user feedback and comments) to find potential requirements for a software system in use. It semi-automates some requirementselicitation tasks using data retrieval and natural language processing (NLP) techniques to extract potential requirements. It supports requirements engineers' efforts to gather potential requirements from crowd-generated data on social networks (e.g., Twitter). It is an assistive approach that taps into unused knowledge and experiences emphasizing continuous requirements elicitation during systems use.

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“…Gebauer et al use content analysis of user reviews to identify functional and non-functional requirements of mobile devices through finding the factors that are significantly related to overall user evaluation [6]. Lee et al elicit customer requirements using their opinions gathered from social network services [7]. Such works capture changing requirements without limited range of users and insufficient expressions.…”

Section: Related Workmentioning

confidence: 99%

“…Several approaches have been developed, regarding the techniques and processes to consolidate, analyze and determine requirements in accordance with online feedback [6][7]. However, these approaches mostly rely on manual content analysis and as such, are not efficient for dealing with large amounts of online reviews in order to shorten time-to-market.…”

Section: Introductionmentioning

confidence: 99%

For User-Driven Software Evolution: Requirements Elicitation Derived from Mining Online Reviews

Jiang

Ruan

Zhang

et al. 2014

Advances in Knowledge Discovery and Data Mining

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Abstract. Online reviews that manifest user feedback have become an available resource for eliciting requirements to design future releases. However, due to complex and diverse opinion expressions, it is challenging to utilize automated analysis for deriving constructive feedback from these reviews. What's more, determining important changes in requirements based on user feedback is also challenging. To address these two problems, this paper proposes a systematic approach for transforming online reviews to evolutionary requirements. According to the characteristics of reviews, we first adapt opinion mining techniques to automatically extract opinion expressions about common software features. To provide meaningful feedback, we then present an optimized method of clustering opinion expressions in terms of a macro network topology. Based on this feedback, we finally combine user satisfaction analysis with the inherent economic attributes associated with the software's revenue to determine evolutionary requirements. Experimental results show that our approach achieves good performance for obtaining constructive feedback even with large amounts of review data, and furthermore discovers the evolutionary requirements that tend to be ignored by developers from a technology perspective.

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Customer Requirements Elicitation based on Social Network Service

Cited by 9 publications

References 8 publications

Social network sites and requirements engineering: A systematic literature review

Social network sites and requirements engineering: A systematic literature review

Crowd-Generated Data Mining for Continuous Requirements Elicitation

For User-Driven Software Evolution: Requirements Elicitation Derived from Mining Online Reviews

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