Reel Life vs. Real Life: How Software Developers Share Their Daily Life
through Vlogs
- URL: http://arxiv.org/abs/2107.07023v2
- Date: Tue, 27 Jul 2021 16:56:46 GMT
- Title: Reel Life vs. Real Life: How Software Developers Share Their Daily Life
through Vlogs
- Authors: Souti Chattopadhyay, Thomas Zimmermann, Denae Ford
- Abstract summary: We analyzed 130 vlogs by software developers on YouTube and conducted a survey with 335 software developers at a large software company.
We found that although vlogs present traditional development activities such as coding and code peripheral activities (11%), they also prominently feature wellness and lifestyle related activities (47.3%)
We also found that developers at the software company were inclined to share more non-coding tasks when asked to create a mock-up vlog to promote diversity.
- Score: 18.33130097682978
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Software developers are turning to vlogs (video blogs) to share what a day is
like to walk in their shoes. Through these vlogs developers share a rich
perspective of their technical work as well their personal lives. However, does
the type of activities portrayed in vlogs differ from activities developers in
the industry perform? Would developers at a software company prefer to show
activities to different extents if they were asked to share about their day
through vlogs? To answer these questions, we analyzed 130 vlogs by software
developers on YouTube and conducted a survey with 335 software developers at a
large software company. We found that although vlogs present traditional
development activities such as coding and code peripheral activities (11%),
they also prominently feature wellness and lifestyle related activities (47.3%)
that have not been reflected in previous software engineering literature. We
also found that developers at the software company were inclined to share more
non-coding tasks (e.g., personal projects, time spent with family and friends,
and health) when asked to create a mock-up vlog to promote diversity. These
findings demonstrate a shift in our understanding of how software developers
are spending their time and find valuable to share publicly. We discuss how
vlogs provide a more complete perspective of software development work and
serve as a valuable source of data for empirical research.
Related papers
- Vlogger: Make Your Dream A Vlog [67.50445251570173]
Vlogger is a generic AI system for generating a minute-level video blog (i.e., vlog) of user descriptions.
We invoke various foundation models to play the critical roles of vlog professionals, including Script, (2) Actor, (3) ShowMaker, and (4) Voicer.
Vlogger can generate over 5-minute vlogs from open-world descriptions, without loss of video coherence on script and actor.
arXiv Detail & Related papers (2024-01-17T18:55:12Z) - With Great Humor Comes Great Developer Engagement [11.367562045401554]
The more engaged developers are, the more value they impart to the software they create.
In this paper, we dive deep into an original vector of engagement - humor - and study how it fuels developer engagement.
We collect data about the humorous elements present within three significant, real-world software projects.
We receive unique insights from 125 developers, who share their real-life experiences with humor in software.
arXiv Detail & Related papers (2023-12-04T07:06:02Z) - Intelligent Software Tooling for Improving Software Development [3.1763879286782966]
Deep Learning (DL) has shown huge advancements in automation across many domains, including Software Development processes.
One of the main reasons behind this success is the availability of large datasets such as open-source code available through GitHub or image datasets of mobile Graphical User Interfaces (GUIs) with RICO and ReDRAW to be trained on.
arXiv Detail & Related papers (2023-10-17T01:29:07Z) - Collaborative, Code-Proximal Dynamic Software Visualization within Code
Editors [55.57032418885258]
This paper introduces the design and proof-of-concept implementation for a software visualization approach that can be embedded into code editors.
Our contribution differs from related work in that we use dynamic analysis of a software system's runtime behavior.
Our visualization approach enhances common remote pair programming tools and is collaboratively usable by employing shared code cities.
arXiv Detail & Related papers (2023-08-30T06:35:40Z) - FLAG3D: A 3D Fitness Activity Dataset with Language Instruction [89.60371681477791]
We present FLAG3D, a large-scale 3D fitness activity dataset with language instruction containing 180K sequences of 60 categories.
We show that FLAG3D contributes great research value for various challenges, such as cross-domain human action recognition, dynamic human mesh recovery, and language-guided human action generation.
arXiv Detail & Related papers (2022-12-09T02:33:33Z) - Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive
Transformer [66.56167074658697]
We present a method that builds on 3D-VQGAN and transformers to generate videos with thousands of frames.
Our evaluation shows that our model trained on 16-frame video clips can generate diverse, coherent, and high-quality long videos.
We also showcase conditional extensions of our approach for generating meaningful long videos by incorporating temporal information with text and audio.
arXiv Detail & Related papers (2022-04-07T17:59:02Z) - Developers Who Vlog: Dismantling Stereotypes through Community and
Identity [18.33130097682978]
We conducted three studies to learn how developers describe a day in their life through vlogs on YouTube.
We interviewed 16 developers who vlogged to identify their motivations for creating this content.
We analyzed 130 vlogs (video blogs) to understand the range of the content conveyed through videos.
arXiv Detail & Related papers (2021-09-13T20:26:41Z) - QVHighlights: Detecting Moments and Highlights in Videos via Natural
Language Queries [89.24431389933703]
We present the Query-based Video Highlights (QVHighlights) dataset.
It consists of over 10,000 YouTube videos, covering a wide range of topics.
Each video in the dataset is annotated with: (1) a human-written free-form NL query, (2) relevant moments in the video w.r.t. the query, and (3) five-point scale saliency scores for all query-relevant clips.
arXiv Detail & Related papers (2021-07-20T16:42:58Z) - What is More Likely to Happen Next? Video-and-Language Future Event
Prediction [111.93601253692165]
Given a video with aligned dialogue, people can often infer what is more likely to happen next.
In this work, we explore whether AI models are able to learn to make such multimodal commonsense next-event predictions.
We collect a new dataset, named Video-and-Language Event Prediction, with 28,726 future event prediction examples.
arXiv Detail & Related papers (2020-10-15T19:56:47Z) - How Gamification Affects Software Developers: Cautionary Evidence from a
Natural Experiment on GitHub [6.123324869194196]
We find that the unannounced removal of daily activity streak counters from the user interface was followed by significant changes in behavior.
Long-running streaks of activity were abandoned and became less common.
We find that some developers abandon a goal to make contributions for 100 days in a row following the removal of the public streak counter.
arXiv Detail & Related papers (2020-06-03T16:35:47Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.