NDLI: Prioritizing user feedback from Twitter: a survey report

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Prioritizing user feedback from Twitter: a survey report

Content Provider	ACM Digital Library
Author	Guzman, Emitza Ibrahim, Mohamed Glinz, Martin
Abstract	Twitter messages (tweets) contain important information for software and requirements evolution, such as feature requests, bug reports and feature shortcoming descriptions. For this reason, Twitter is an important source for crowd-based requirements engineering and software evolution. However, a manual analysis of this information is unfeasible due to the large number of tweets, its unstructured nature and varying quality. Therefore, automatic analysis techniques are needed for, e.g., summarizing, classifying and prioritizing tweets. In this work we present a survey with 84 software engineering practitioners and researchers that studies the tweet attributes that are most telling of tweet priority when performing software evolution tasks. We believe that our results can be used to implement mechanisms for prioritizing user feedback with social components. Thus, it can be helpful for enhancing crowd-based requirements engineering and software evolution.
Starting Page	21
Ending Page	24
Page Count	4
File Format	PDF
ISBN	9781538640418
DOI	10.1109/CSI-SE.2017.4
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-05-20
Access Restriction	Subscribed
Subject Keyword	Crowd-based requirements engineering Crowd-based software evolution User feedback
Content Type	Text
Resource Type	Article

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