Temporal Drift of Emoji Sentiment in GitHub Issue Titles
Tracking how the emotional tone of GitHub issue titles changes over time.
- Observations
- 32
- Tracking since
- Last updated
Average Emoji Sentiment Score
The average sentiment score of emojis found in GitHub issue titles within a repository/overall.
- torvalds
- microsoft
- apache
- apple
- kubernetes
- tensorflow
- torvalds1 score
- microsoft0.1 score
- apache0 score
- apple0 score
- facebook0 score
- google0 score
- kubernetes0 score
- tensorflow0 score
| When | Series | Average Emoji Sentiment Score |
|---|---|---|
| torvalds | 1 score | |
| microsoft | 0.1 score | |
| apache | 0 score | |
| apple | 0 score | |
| 0 score | ||
| 0 score | ||
| kubernetes | 0 score | |
| tensorflow | 0 score | |
| torvalds | 1 score | |
| microsoft | 0.1 score | |
| apache | 0 score | |
| apple | 0 score | |
| 0 score | ||
| 0 score | ||
| kubernetes | 0 score | |
| tensorflow | 0 score |
Proportion of Issue Titles with Emojis
The percentage of GitHub issue titles that contain at least one emoji.
- torvalds
- microsoft
- apache
- apple
- kubernetes
- tensorflow
- torvalds5.0%
- microsoft3.0%
- google2.0%
- facebook1.0%
- apache0.0%
- apple0.0%
- kubernetes0.0%
- tensorflow0.0%
| When | Series | Proportion of Issue Titles with Emojis |
|---|---|---|
| torvalds | 5.0% | |
| microsoft | 3.0% | |
| 2.0% | ||
| 1.0% | ||
| apache | 0.0% | |
| apple | 0.0% | |
| kubernetes | 0.0% | |
| tensorflow | 0.0% | |
| torvalds | 5.0% | |
| microsoft | 3.0% | |
| 2.0% | ||
| 1.0% | ||
| apache | 0.0% | |
| apple | 0.0% | |
| kubernetes | 0.0% | |
| tensorflow | 0.0% |
About this data
This page explores the 'temporal drift' of emoji sentiment found within the titles of GitHub issue reports. We analyse the average sentiment score of emojis used in titles, offering a unique insight into how developers and users feel about reported bugs and feature requests over time. This metric is novel as it specifically contextualises emoji sentiment within the technical domain of software development, an area not typically covered by general sentiment analysis tools.
Our data is derived from publicly available GitHub issue titles across various repositories. We calculate the proportion of titles that include emojis and the average sentiment score of those emojis. This provides a nuanced view beyond simple emoji counts, highlighting shifts in community mood, frustration, or enthusiasm as software evolves. Understanding this can help project maintainers better gauge community reception and prioritise work.
Sources
Every figure on this page was read from these pages.
- https://api.github.com/search/issues?q=is:issue+is:open+org:torvalds&per_page=100&sort=created
- https://api.github.com/search/issues?q=is:issue+is:open+org:microsoft&per_page=100&sort=created
- https://api.github.com/search/issues?q=is:issue+is:open+org:google&per_page=100&sort=created
- https://api.github.com/search/issues?q=is:issue+is:open+org:facebook&per_page=100&sort=created
- https://api.github.com/search/issues?q=is:issue+is:open+org:apple&per_page=100&sort=created
- https://api.github.com/search/issues?q=is:issue+is:open+org:apache&per_page=100&sort=created
- https://api.github.com/search/issues?q=is:issue+is:open+org:kubernetes&per_page=100&sort=created
- https://api.github.com/search/issues?q=is:issue+is:open+org:tensorflow&per_page=100&sort=created
Why this isn't published anywhere else
While direct tracking of temporal emoji sentiment drift *specifically in GitHub issue titles* is not evident, there is substantial related research on emoji semantic drift (often on Twitter), emotional contagion on GitHub, and the impact of emojis on issue resolution, indicating the underlying concepts are explored. Existing work touches upon emoji sentiment and temporal aspects but not precisely this combined metric and context.
Uniqueness score 0.70 — assessed against live web search results when this subject was created.