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Title:Constructing a dataset to support agent-based modeling of online interactions : users, topics, and interaction networks
Authors:ID Sittar, Abdul, Institut "Jožef Stefan" (Author)
ID Češnovar, Miha (Author)
ID Guček, Alenka, Institut "Jožef Stefan" (Author)
ID Grobelnik, Marko, Institut "Jožef Stefan" (Author)
Files:URL URL - Source URL, visit https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11457911
 
.pdf PDF - Presentation file, download (4,16 MB)
MD5: 72C35B7A44D9BE5FA7A0AB9300664A3A
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo IJS - Jožef Stefan Institute
Abstract:Agent-based modeling (ABM) provides a powerful framework for exploring how individual behaviors and interactions give rise to collective social dynamics. However, most ABMs rely on handcrafted or parameterized agent rules that are not empirically grounded, thereby limiting their realism and validation against observed data. To address this gap, we constructed a large-scale, empirically grounded dataset from Reddit to support the development and evaluation of agent-based social simulations. The dataset includes 33 technology-focused, 14 climate-focused, and 7 COVID-related aggregated agents, encompassing around one million posts and comments. Using publicly available posts and comments, we define agent categories based on content and interaction patterns, derive inter-agent relationships from temporal commenting behaviors, and build a directed, weighted network that reflects empirically observed user connections. The resulting dataset enables researchers to calibrate and benchmark agent behavior, network structure, and information diffusion processes against real social dynamics. Our quantitative analysis reveals clear topic-dependent differences in how users interact. Climate discussions show dense, highly connected networks with sustained engagement, COVID-related interactions are sparse and mostly one-directional, and technology discussions are organized around a small number of central hubs. Manual qualitative analysis further shows that agent interactions follow realistic patterns of timing, similarity between users, and sentiment change.
Keywords:agent-based modeling, online social interactions, information diffusion, network structure analysis, homophily, reddit discussion networks
Publication status:Published
Publication version:Version of Record
Submitted for review:15.01.2026
Article acceptance date:26.03.2026
Publication date:09.04.2026
Publisher:IEEE
Year of publishing:2026
Number of pages:str. 52890-52810
Numbering:Vol. 14
Source:ZDA
PID:20.500.12556/DiRROS-29228 New window
UDC:004
ISSN on article:2169-3536
DOI:10.1109/ACCESS.2026.3679263 New window
COBISS.SI-ID:276633091 New window
Copyright:© 2026 The Authors.
Note:Nasl. z nasl. zaslona; Soavtorji: Miha Češnovar, Alenka Guček, Marko Grobelnik; Opis vira z dne 28. 4. 2026;
Publication date in DiRROS:28.04.2026
Views:55
Downloads:24
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Record is a part of a journal

Title:IEEE access
Publisher:Institute of Electrical and Electronics Engineers
ISSN:2169-3536
COBISS.SI-ID:519839513 New window

Document is financed by a project

Funder:EC - European Commission
Project number:101095095
Name:TWin of Online Social Networks
Acronym:TWON

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:09.04.2026
Applies to:VoR

Secondary language

Language:Slovenian
Keywords:agentno modeliranje, spletne družbene interakcije, širjenje informacij, analiza omrežne strukture, homofilija, omrežja razprav na Redditu


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