{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T14:02:54Z","timestamp":1776780174086,"version":"3.51.2"},"reference-count":43,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T00:00:00Z","timestamp":1730851200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science Centre, Poland","award":["2022\/45\/B\/ST6\/04145"],"award-info":[{"award-number":["2022\/45\/B\/ST6\/04145"]}]},{"name":"National Science Centre, Poland","award":["101086321 OMINO"],"award-info":[{"award-number":["101086321 OMINO"]}]},{"name":"Polish Ministry of Education and Science","award":["2022\/45\/B\/ST6\/04145"],"award-info":[{"award-number":["2022\/45\/B\/ST6\/04145"]}]},{"name":"Polish Ministry of Education and Science","award":["101086321 OMINO"],"award-info":[{"award-number":["101086321 OMINO"]}]},{"name":"Horizon Europe","award":["2022\/45\/B\/ST6\/04145"],"award-info":[{"award-number":["2022\/45\/B\/ST6\/04145"]}]},{"name":"Horizon Europe","award":["101086321 OMINO"],"award-info":[{"award-number":["101086321 OMINO"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The identification of key nodes in complex networks is an important topic in many network science areas. It is vital to a variety of real-world applications, including viral marketing, epidemic spreading and influence maximization. In recent years, machine learning algorithms have proven to outperform the conventional, centrality-based methods in accuracy and consistency, but this approach still requires further refinement. What information about the influencers can be extracted from the network? How can we precisely obtain the labels required for training? Can these models generalize well? In this paper, we answer these questions by presenting an enhanced machine learning-based framework for the influence spread problem. We focus on identifying key nodes for the Independent Cascade model, which is a popular reference method. Our main contribution is an improved process of obtaining the labels required for training by introducing \u201cSmart Bins\u201d and proving their advantage over known methods. Next, we show that our methodology allows ML models to not only predict the influence of a given node, but to also determine other characteristics of the spreading process\u2014which is another novelty to the relevant literature. Finally, we extensively test our framework and its ability to generalize beyond complex networks of different types and sizes, gaining important insight into the properties of these methods.<\/jats:p>","DOI":"10.3390\/e26110955","type":"journal-article","created":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T11:13:37Z","timestamp":1730891617000},"page":"955","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Identifying Key Nodes for the Influence Spread Using a Machine Learning Approach"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8870-3394","authenticated-orcid":false,"given":"Mateusz","family":"Stolarski","sequence":"first","affiliation":[{"name":"Department of Artificial Intelligence, Wroc\u0142aw University of Science and Technology, 50-370 Wroc\u0142aw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam","family":"Pir\u00f3g","sequence":"additional","affiliation":[{"name":"4Semantics, 00-833 Warszawa, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6474-0089","authenticated-orcid":false,"given":"Piotr","family":"Br\u00f3dka","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence, Wroc\u0142aw University of Science and Technology, 50-370 Wroc\u0142aw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.physa.2013.12.049","article-title":"A social force evacuation model with the leadership effect","volume":"400","author":"Hou","year":"2014","journal-title":"Phys. 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