research-article

Recommending Who to Follow in the Software Engineering Twitter Space

Authors:

Abhishek Sharma,

Dinusha Wijedasa,

David LoAuthors Info & Claims

ACM Transactions on Software Engineering and Methodology (TOSEM), Volume 27, Issue 4

Article No.: 16, Pages 1 - 33

https://doi.org/10.1145/3266426

Published: 22 October 2018 Publication History

Abstract

With the advent of social media, developers are increasingly using it in their software development activities. Twitter is one of the popular social mediums used by developers. A recent study by Singer et al. found that software developers use Twitter to “keep up with the fast-paced development landscape.” Unfortunately, due to the general-purpose nature of Twitter, it’s challenging for developers to use Twitter for their development activities. Our survey with 36 developers who use Twitter in their development activities highlights that developers are interested in following specialized software gurus who share relevant technical tweets.

To help developers perform this task, in this work we propose a recommendation system to identify specialized software gurus. Our approach first extracts different kinds of features that characterize a Twitter user and then employs a two-stage classification approach to generate a discriminative model, which can differentiate specialized software gurus in a particular domain from other Twitter users that generate domain-related tweets (aka domain-related Twitter users). We have investigated the effectiveness of our approach in finding specialized software gurus for four different domains (JavaScript, Android, Python, and Linux) on a dataset of 86,824 Twitter users who generate 5,517,878 tweets over 1 month. Our approach can differentiate specialized software experts from other domain-related Twitter users with an F-Measure of up to 0.820. Compared with existing Twitter domain expert recommendation approaches, our proposed approach can outperform their F-Measure by at least 7.63%.

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Cited By

Islam SNugroho YShahrear CWahed NGunawan DWahyu Pamungkas EHumayun Kabir MIndra Kurniawan YUddin M(2024)An empirical study of software ecosystem related tweets by npm maintainersPeerJ Computer Science10.7717/peerj-cs.166910(e1669)Online publication date: 17-Jan-2024
https://doi.org/10.7717/peerj-cs.1669
Nematova GRehman MAmin AHashmani M(2020)Review of Social Media Influence on Software DevelopmentMehran University Research Journal of Engineering and Technology10.22581/muet1982.2003.1539:3(603-611)Online publication date: 1-Jul-2020
https://doi.org/10.22581/muet1982.2003.15
Jiang JLo DYang YLi JZhang L(2019)A first look at unfollowing behavior on GitHubInformation and Software Technology10.1016/j.infsof.2018.08.012105(150-160)Online publication date: Jan-2019
https://doi.org/10.1016/j.infsof.2018.08.012
Show More Cited By

Index Terms

Recommending Who to Follow in the Software Engineering Twitter Space
1. Software and its engineering
  1. Software creation and management
    1. Collaboration in software development

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cover image ACM Transactions on Software Engineering and Methodology

ACM Transactions on Software Engineering and Methodology Volume 27, Issue 4

October 2018

159 pages

ISSN:1049-331X

EISSN:1557-7392

DOI:10.1145/3287303

Editor:
David S. Rosenblum
National University of Singapore, Singapore

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Copyright © 2018 ACM.

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Publication History

Published: 22 October 2018

Accepted: 01 July 2018

Revised: 01 March 2018

Received: 01 June 2016

Published in TOSEM Volume 27, Issue 4

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Cited By

Islam SNugroho YShahrear CWahed NGunawan DWahyu Pamungkas EHumayun Kabir MIndra Kurniawan YUddin M(2024)An empirical study of software ecosystem related tweets by npm maintainersPeerJ Computer Science10.7717/peerj-cs.166910(e1669)Online publication date: 17-Jan-2024
https://doi.org/10.7717/peerj-cs.1669
Nematova GRehman MAmin AHashmani M(2020)Review of Social Media Influence on Software DevelopmentMehran University Research Journal of Engineering and Technology10.22581/muet1982.2003.1539:3(603-611)Online publication date: 1-Jul-2020
https://doi.org/10.22581/muet1982.2003.15
Jiang JLo DYang YLi JZhang L(2019)A first look at unfollowing behavior on GitHubInformation and Software Technology10.1016/j.infsof.2018.08.012105(150-160)Online publication date: Jan-2019
https://doi.org/10.1016/j.infsof.2018.08.012
Sulistya APrana GSharma ALo DTreude C(2019)SIEVE: Helping developers sift wheat from chaff via cross-platform analysisEmpirical Software Engineering10.1007/s10664-019-09775-w25:1(996-1030)Online publication date: 2-Oct-2019
https://dl.acm.org/doi/10.1007/s10664-019-09775-w

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