Relational event models in network science
Bibliographic Data
| ID | 6161669 |
|---|---|
| Authors | C T Butts (0000-0002-7911-9834, University of California, Irvine), A Lomi (0000-0002-2858-0022, Università della Svizzera italiana), Tom Ab Snijders (0000-0003-3157-4157, University of Oxford), C Stadtfeld (0000-0002-2704-2134, ETH Zurich, corresponding author) |
| Year | 2023 |
| Volume | 11 |
| Issue | 2 |
| Pages | 175-183 |
| Publication date | 2023-05-08 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Network Science (JOURNAL) |
| Journal identifiers | ISSN: 2050-1250 • E-ISSN: 2050-1242 |
| Publisher | Cambridge University Press (PUBLISHER • US) |
| DOI | 10.1017/nws.2023.9 |
| OpenAlex | W4376862950 |
| Language | EN |
| Citations received | 12 |
| References cited | 58 |
Relational event models (REMs) for the analysis of social interaction were first introduced 15 years ago. Since then, a number of important substantive and methodological contributions have produced their progressive refinement and hence facilitated their increased adoption in studies of social and other networks. Today REMs represent a well-established class of statistical models for relational processes. This special issue of Network Science demonstrates the standing and recognition that REMs have achieved within the network analysis and networks science communities. We wrote this brief introductory editorial essay with four main objectives in mind: (i) positioning relational event data and models in the larger context of contemporary network science and social network research; (ii) reviewing some of the most important recent developments; (iii) presenting the innovative studies collected in this special issue as evidence of the empirical value of REMs, and (iv) identifying open questions and future research directions
Biology · Class (philosophy · Cognitive science · Complex network · Context (archaeology · Data science · Event (particle physics · Network science · Social media · Social network (sociolinguistics · Social network analysis · World Wide Web · Complex Network Analysis Techniques · Computer Science · Mental Health Research Topics · Opinion Dynamics and Social Influence · Psychology · Artificial Intelligence
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Lost in translation
| Unique citing works | 12 |
|---|---|
| Citations per year | 6 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 12 |