How Do Developers Blog?

2021 ◽  
Vol 46 (3) ◽  
pp. 26-29
Author(s):  
Dennis Pagano ◽  
Walid Maalej
Keyword(s):  
Social Media ◽  
Software Engineering ◽  
Knowledge Sharing ◽  
Mining Software Repositories ◽  
Version Control ◽  
Software Repositories

A decade ago, the rise of GitHub and StackOverflow as social version control and knowledge sharing environments was about to start. Social media like Twitter were mocked by some software engineering researchers and practitioners as "tools for kids not professionals". At that time, we published one of the first papers [12] on social media in software engineering at MSR 2011, the Mining Software Repositories Conference.

Automatically Labelled Software Topic Model

2020 ◽  
Vol 11 (1) ◽  
pp. 57-78
Author(s):  
Youcef Bouziane ◽  
Mustapha Kamel Abdi ◽  
Salah Sadou
Keyword(s):  
Information Retrieval ◽  
Software Engineering ◽  
Topic Model ◽  
Mining Software Repositories ◽  
Valuable Data ◽  
Empirical Results ◽  
Software Repositories ◽  
Manual Analysis ◽  
Novel Approach ◽  
Support Software

Public software repositories (SR) maintain a massive amount of valuable data offering opportunities to support software engineering (SE) tasks. Researchers have applied information retrieval techniques in mining software repositories. Topic models are one of these techniques. However, this technique does not give an interpretation nor labels to the extracted topics and it requires manual analysis to identify them. Some approaches were proposed to automatically label the topics using tags in SR, but they do not consider the existence of spam-tags and they have difficulties to scale to large tag space. This article introduces a novel approach called automatically labelled software topic model (AL-STM) that labels the topics based on observed tags in SR. It mitigates the shortcomings of manual and automatic labelling of topics in SE. AL-STM is implemented using 22K GitHub projects and evaluated in a SE task (tag recommending) against the currently used techniques. The empirical results suggest that AL-STM is more robust in terms of MAP and nDCG, and more scalable to large tag space.

scholarly journals “Why not use it more?” Sources of self-efficacy in researchers’ use of social media for knowledge sharing

2018 ◽  
Vol 74 (6) ◽  
pp. 1274-1292 ◽  
Author(s):  
Hussain Alshahrani ◽  
Diane Rasmussen Pennington
Keyword(s):  
Social Media ◽  
Knowledge Sharing ◽  
Self Efficacy ◽  
Academic Staff ◽  
Structured Interviews ◽  
Content Type ◽  
Personal Mastery ◽  
Mastery Experience ◽  
Use Of Social Media ◽  
Postdoctoral Researchers

Purpose The purpose of this paper is to investigate the sources of self-efficacy that researchers rely on when using social media for knowledge sharing and to explore how these sources impact their use. Design/methodology/approach The study employed 30 semi-structured interviews with researchers at a major Scottish university. The authors analysed the interview transcriptions using directed content analysis. Findings The researchers relied on the four sources of self-efficacy proposed by Bandura (1977) when using social media for knowledge sharing. These sources lead researchers to use social media effectively and frequently for sharing knowledge, although some may discourage its use. Research limitations/implications It extends the self-efficacy integrative theoretical framework of Bandura (1977) by presenting the relative amount of the influence of these sources for researchers to share their ideas, experiences, questions and research outputs on social media. While the participants included academic staff, postdoctoral researchers, and PhD students, the majority were PhD students. Practical implications The findings can help universities understand how to promote productive use of social media. For example, academic staff who have high personal mastery experience could mentor those who do not. Originality/value This is the first known study to investigate the sources of self-efficacy that impact researchers’ use of social media for knowledge sharing.

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