{
  "annotation_id": "f119565d-96aa-4c6e-934c-79540adbc767",
  "date_created": "2026-03-02T18:01:14.144000Z",
  "date_modified": "2026-03-02T18:01:14.144000Z",
  "file_hash": "16d8be3688a9c82f6d543455472c12ff8a9c5715b071c0a2cd432924bdfb3d08",
  "private": false,
  "record": {
    "abstract": "The dynamics of a wide range of real systems, from email patterns to\nearthquakes, display a bursty, intermittent nature, characterized by short\ntimeframes of intensive activity followed by long times of no or reduced\nactivity. The understanding of the origin of such bursty patterns is hindered\nby the lack of tools to compare different systems using a common framework. We\nintroduce two measures to distinguish the mechanisms responsible for the bursty\nnature of real signals, changes in the interevent times and memory. We find\nthat while the burstiness of natural phenomena is rooted in both the interevent\ntime distribution and memory, for human dynamics memory is weak, and the bursty\ncharacter is due to changes in the interevent time distribution. Finally, we\nshow that current models lack in their ability to reproduce the activity\npattern observed in real systems, opening up new avenues for future work.",
    "arxiv_id": "physics/0610233",
    "authors": [
      "Kwang-Il Goh",
      "Albert-Laszlo Barabasi"
    ],
    "categories": [
      "physics.data-an"
    ],
    "title": "Burstiness and Memory in Complex Systems",
    "url": "https://arxiv.org/abs/physics/0610233"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "c595760b-1992-444f-acae-0ab79e746e6c",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}