Conference proceeding
Software-related Slack Chats with Disentangled Conversations
Proceedings of the 17th International Conference on Mining Software Repositories, pp 588-592
29 Jun 2020
Abstract
More than ever, developers are participating in public chat communities to ask and answer software development questions. With over ten million daily active users, Slack is one of the most popular chat platforms, hosting many active channels focused on software development technologies, e.g., python, react. Prior studies have shown that public Slack chat transcripts contain valuable information, which could provide support for improving automatic software maintenance tools or help researchers understand developer struggles or concerns.
In this paper, we present a dataset of software-related Q&A chat conversations, curated for two years from three open Slack communities (python, clojure, elm). Our dataset consists of 38,955 conversations, 437,893 utterances, contributed by 12,171 users. We also share the code for a customized machine-learning based algorithm that automatically extracts (or disentangles) conversations from the downloaded chat transcripts.
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Details
- Title
- Software-related Slack Chats with Disentangled Conversations
- Creators
- Preetha Chatterjee - University of DelawareKostadin Damevski - Virginia Commonwealth UniversityNicholas A. Kraft - Uservoice, Raleigh, NC, USALori Pollock - University of Delaware
- Publication Details
- Proceedings of the 17th International Conference on Mining Software Repositories, pp 588-592
- Conference
- MSR '20: 17th International Conference on Mining Software Repositories
- Series
- ACM Conferences
- Publisher
- ACM
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Web of Science ID
- WOS:001017777500067
- Scopus ID
- 2-s2.0-85093672422
- Other Identifier
- 991021883914904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Software Engineering