{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T15:51:15Z","timestamp":1753890675352,"version":"3.41.2"},"reference-count":146,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,12,2]],"date-time":"2022-12-02T00:00:00Z","timestamp":1669939200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Big Data"],"abstract":"<jats:p>Graph structures have attracted much research attention for carrying complex relational information. Based on graphs, many algorithms and tools are proposed and developed for dealing with real-world tasks such as recommendation, fraud detection, molecule design, etc. In this paper, we first discuss three topics of graph research, i.e., graph mining, graph representations, and graph neural networks (GNNs). Then, we introduce the definitions of <jats:italic>natural dynamics<\/jats:italic> and <jats:italic>artificial dynamics<\/jats:italic> in graphs, and the related works of natural and artificial dynamics about how they boost the aforementioned graph research topics, where we also discuss the current limitation and future opportunities.<\/jats:p>","DOI":"10.3389\/fdata.2022.1062637","type":"journal-article","created":{"date-parts":[[2022,12,2]],"date-time":"2022-12-02T19:52:22Z","timestamp":1670010742000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Natural and Artificial Dynamics in Graphs: Concept, Progress, and Future"],"prefix":"10.3389","volume":"5","author":[{"given":"Dongqi","family":"Fu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingrui","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2022,12,2]]},"reference":[{"key":"B1","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1145\/2976749.2978318","article-title":"\u201cDeep learning with differential privacy,\u201d","volume-title":"CCS '16: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (SIGSAC 2016)","author":"Abadi","year":"2016"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2601412","article-title":"Evolutionary network analysis: a survey","volume":"47","author":"Aggarwal","year":"2014","journal-title":"ACM Comput. 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