Dataset Information

Status, identity, and language: A study of issue discussions in GitHub.

ABSTRACT: Successful open source software (OSS) projects comprise freely observable, task-oriented social networks with hundreds or thousands of participants and large amounts of (textual and technical) discussion. The sheer volume of interactions and participants makes it challenging for participants to find relevant tasks, discussions and people. Tagging (e.g., @AmySmith) is a socio-technical practice that enables more focused discussion. By tagging important and relevant people, discussions can be advanced more effectively. However, for all but a few insiders, it can be difficult to identify important and/or relevant people. In this paper we study tagging in OSS projects from a socio-linguistics perspective. First we argue that textual content per se reveals a great deal about the status and identity of who is speaking and who is being addressed. Next, we suggest that this phenomenon can be usefully modeled using modern deep-learning methods. Finally, we illustrate the value of these approaches with tools that could assist people to find the important and relevant people for a discussion.

SUBMITTER: Liao J

PROVIDER: S-EPMC6568400 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Status, identity, and language: A study of issue discussions in GitHub.

Liao Jingxian J Yang Guowei G Kavaler David D Filkov Vladimir V Devanbu Prem P

PloS one 20190614 6

Successful open source software (OSS) projects comprise freely observable, task-oriented social networks with hundreds or thousands of participants and large amounts of (textual and technical) discussion. The sheer volume of interactions and participants makes it challenging for participants to find relevant tasks, discussions and people. Tagging (e.g., @AmySmith) is a socio-technical practice that enables more focused discussion. By tagging important and relevant people, discussions can be adva ...[more]

PMID: 31199802

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Project description:ObjectivesIn the context of serious or life-limiting illness, pediatric patients and their families are faced with difficult decisions surrounding appropriate resuscitation efforts in the event of a cardiopulmonary arrest. Code status orders are one way to inform end-of-life medical decision making. The objectives of this study are to evaluate the extent to which pediatric providers have knowledge of code status options and explore the association of provider role with (1) knowledge of code status options, (2) perception of timing of code status discussions, (3) perception of family receptivity to code status discussions, and (4) comfort carrying out code status discussions.DesignNurses, trainees (residents and fellows), and attending physicians from pediatric units where code status discussions typically occur completed a short survey questionnaire regarding their knowledge of code status options and perceptions surrounding code status discussions.SettingSingle center, quaternary care children's hospital.Measurements and main results203 nurses, 31 trainees, and 29 attending physicians in 4 high-acuity pediatric units responded to the survey (N = 263, 90% response rate). Based on an objective knowledge measure, providers demonstrate poor understanding of available code status options, with only 22% of providers able to enumerate more than two of four available code status options. In contrast, provider groups self-report high levels of familiarity with available code status options, with attending physicians reporting significantly higher levels than nurses and trainees (p = 0.0125). Nurses and attending physicians show significantly different perception of code status discussion timing, with majority of nurses (63.4%) perceiving discussions as occurring "too late" or "much too late" and majority of attending physicians (55.6%) perceiving the timing as "about right" (p<0.0001). Attending physicians report significantly higher comfort having code status discussions with families than do nurses or trainees (p≤0.0001). Attending physicians and trainees perceive families as more receptive to code status discussions than nurses (p<0.0001 and p = 0.0018, respectively).ConclusionsProviders have poor understanding of code status options and differ significantly in their comfort having code status discussions and their perceptions of these discussions. These findings may reflect inherent differences among providers, but may also reflect discordant visions of appropriate care and function as a potential source of moral distress. Lack of knowledge of code status options and differences in provider perceptions are likely barriers to quality communication surrounding end-of-life options.

Project description:In recent years, the explosion of genomic data and bioinformatic tools has been accompanied by a growing conversation around reproducibility of results and usability of software. However, the actual state of the body of bioinformatics software remains largely unknown. The purpose of this paper is to investigate the state of source code in the bioinformatics community, specifically looking at relationships between code properties, development activity, developer communities, and software impact. To investigate these issues, we curated a list of 1,720 bioinformatics repositories on GitHub through their mention in peer-reviewed bioinformatics articles. Additionally, we included 23 high-profile repositories identified by their popularity in an online bioinformatics forum. We analyzed repository metadata, source code, development activity, and team dynamics using data made available publicly through the GitHub API, as well as article metadata. We found key relationships within our dataset, including: certain scientific topics are associated with more active code development and higher community interest in the repository; most of the code in the main dataset is written in dynamically typed languages, while most of the code in the high-profile set is statically typed; developer team size is associated with community engagement and high-profile repositories have larger teams; the proportion of female contributors decreases for high-profile repositories and with seniority level in author lists; and, multiple measures of project impact are associated with the simple variable of whether the code was modified at all after paper publication. In addition to providing the first large-scale analysis of bioinformatics code to our knowledge, our work will enable future analysis through publicly available data, code, and methods. Code to generate the dataset and reproduce the analysis is provided under the MIT license at https://github.com/pamelarussell/github-bioinformatics. Data are available at https://doi.org/10.17605/OSF.IO/UWHX8.

Dataset Information

Status, identity, and language: A study of issue discussions in GitHub.

Publications

Status, identity, and language: A study of issue discussions in GitHub.

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