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Prioritizing User Feedback from Twitter: A Survey Report

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE/ACM 4th International Workshop on CrowdSourcing in Software Engineering, CSI-SE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages21-24
Number of pages4
ISBN (Electronic)9781538640418
DOIs
Publication statusPublished - 7 Jul 2017
Externally publishedYes
Event4th IEEE/ACM International Workshop on CrowdSourcing in Software Engineering, CSI-SE 2017 - Buenos Aires, Argentina
Duration: 22 May 2017 → …

Publication series

NameProceedings - 2017 IEEE/ACM 4th International Workshop on CrowdSourcing in Software Engineering, CSI-SE 2017

Conference

Conference4th IEEE/ACM International Workshop on CrowdSourcing in Software Engineering, CSI-SE 2017
Country/TerritoryArgentina
CityBuenos Aires
Period22/05/17 → …

Funding

FundersFunder number
Horizon 2020 Framework Programme644018

    Keywords

    • crowd-based requirements engineering
    • crowd-based software evolution
    • user feedback

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