--- language: - en license: apache-2.0 task_categories: - time-series-forecasting tags: - temporal-point-process - event-sequences - github - software-engineering - developer-workflows - marked-temporal-point-process size_categories: - n<1K --- # GitHub User Event Streams Curated event sequences from individual GitHub developers, designed for temporal point process (TPP) and marked temporal point process (MTPP) modeling. Each sequence captures a single developer's activity across multiple repositories over a one-week window. ## Dataset Description - **Source:** [GH Archive](https://www.gharchive.org/) raw JSON dumps - **Time window:** June 1 - 7, 2024 - **Grouping:** Events grouped by user (actor) - **Sequences:** ~382 - **Sequence length:** 80-100 events per sequence - **Time unit:** hours - **Language:** English only ## Schema Each record is a dictionary with 8 fields: | Field | Type | Description | |---|---|---| | `seq_idx` | int | Sequence index | | `seq_len` | int | Number of events in the sequence | | `description` | str | User name, active repos (with descriptions), and event window | | `metadata` | str (JSON) | `actor_login`, `num_repos`, `top_repos`, `time_unit` | | `time_since_start` | list[float] | Time since the first event (in `time_unit`, default hours) | | `time_since_last_event` | list[float] | Time since the previous event (in `time_unit`, default hours) | | `type_event` | list[str] | Event type labels (see below) | | `type_text` | list[str] | Natural language description of each event | ## Event Types (8 categories) | Label | Description | |---|---| | `issue_opened` | New issue filed | | `issue_closed` | Issue resolved/closed | | `pr_opened` | Pull request opened | | `pr_merged` | Pull request merged | | `push` | Code pushed (with commit messages) | | `release` | Release published | | `pr_reviewed` | PR approved or changes requested | | `comment` | Comment on issue, PR, or review | ## Curation Filters Sequences are selected to represent moderately active developers working across a focused set of repositories: | Filter | Value | Description | |---|---|---| | `min-raw-events` | 50 | Min kept-type events in archive (pre-classification) | | `max-raw-events` | 300 | Max kept-type events in archive (pre-classification) | | `min-events` | 80 | Min classified events per sequence | | `max-events` | 100 | Max classified events (skip, not truncate) | | `min-unique-types` | 5 | At least 5 distinct event types | | `min-repos` | 2 | Active in at least 2 repos | | `max-repos` | 5 | Active in at most 5 repos | | `min-avg-text-len` | 150 | Min average text length per event | | `max-type-fraction` | 0.5 | No single event type >50% of events | | `require-english` | true | All event texts must be in English (non-Latin script detection) | Additional processing: - Bot users are excluded (detected by name patterns like `[bot]`, `dependabot`, etc.) - Consecutive duplicate events (same type + text) are deduplicated ## Key Difference from Repository Events | | User Events | Repo Events | |---|---|---| | Grouping | By developer | By repository | | Cross-repo | Yes (2-5 repos) | No (single repo) | | Text perspective | Mentions repository name | Mentions actor name | | Use case | Developer workflow modeling | Project activity modeling | ## Example ```json { "seq_idx": 0, "seq_len": 90, "description": "GitHub user alice: active in org/repo-a (A web framework for Rust), org/repo-b Event window: June 02 - 07, 2024.", "metadata": "{\"actor_login\": \"alice\", \"num_repos\": 2, \"top_repos\": [\"org/repo-a\", \"org/repo-b\"], \"time_unit\": \"hours\"}", "time_since_start": [0.0, 0.004, ...], "time_since_last_event": [0.0, 0.004, ...], "type_event": ["pr_reviewed", "pr_merged", "push", ...], "type_text": ["PR approved in org/repo-a: Add new feature...", ...] } ``` ## Intended Use - Training and evaluating temporal point process models - Studying individual developer workflow patterns across repos - Benchmarking next-event prediction and event forecasting - Modeling marked temporal point processes with rich text marks ## Citation If you use this dataset, please cite: ```bibtex @dataset{github_user_events_2024, title={GitHub User Event Streams}, author={XiaoBB}, year={2024}, url={https://huggingface.co/datasets/XiaoBB/github_user_events}, note={Curated from GH Archive, June 2024} } ```