Preprocessing Role in Analyzing Tweets Towards Requirement Engineering

Ebrahimi, Amir Mohammad; Barforoush, Ahmad Abdollahzadeh

doi:10.1109/iraniancee.2019.8786652

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…Ebrahimi and Barforoush 60 have proposed an approach that involved more than 6000 experiments to analyze the effects of 11 data preprocessing techniques on the classification performance of requirements elicitation‐related tweets. The authors trained and tested multinomial NB, decision tree (DT), and RF algorithms on a dataset of 4000 tweets as a sample of twitter feeds.…”

Section: Resultsmentioning

confidence: 99%

“…Automatically processing unstructured data is another challenge identified in our selected studies. The SNS users express their opinion in unconventional manners that makes automatic processing of opinions as difficult as possible 43,60 . In order to cope with such issues, technical opinion mining and NLP techniques should be integrated in order to deal with such kind of unstructured data.…”

Section: Resultsmentioning

confidence: 99%

“…Table 5 shows that authors in previous studies [34][35][36]38,40,[47][48][49]51,52,60 used Twitter as a platform to elicit user requirements while other works [41][42][43] used both Twitter and Facebook as platforms to elicit user requirements. Kanchev et al 46 have used Reddit as a platform to elicit user requirements.…”

Section: What Re Activity(s) Can Be Supported By Sns? (Rq2)mentioning

confidence: 99%

“…Nayebi et al 63 presented a tool named as MAPFEAT to support requirements elicitation and negotiation activities. Ebrahimi and Barforoush 60 have also adopted an automatic approach to support the requirements elicitation activity of RE. Stanik and Maalej 59 presented a tool that supports continuous elicitation of user requirements from SNS.…”

Section: What Re Activity(s) Can Be Supported By Sns? (Rq2)mentioning

confidence: 99%

“…The SNS users express their opinion in unconventional manners that makes automatic processing of opinions as difficult as possible. 43,60 In order to cope with such issues, technical opinion mining and NLP techniques should be integrated in order to deal with such kind of unstructured data. The volume of SNS user-generated data is huge.…”

Section: What Re Activity(s) Can Be Supported By Sns? (Rq2)mentioning

confidence: 99%

See 4 more Smart Citations

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%

Section: Resultsmentioning

confidence: 99%