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Naslov:Constructing a dataset to support agent-based modeling of online interactions : users, topics, and interaction networks
Avtorji:ID Sittar, Abdul, Institut "Jožef Stefan" (Avtor)
ID Češnovar, Miha (Avtor)
ID Guček, Alenka, Institut "Jožef Stefan" (Avtor)
ID Grobelnik, Marko, Institut "Jožef Stefan" (Avtor)
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11457911
 
.pdf PDF - Predstavitvena datoteka, prenos (4,16 MB)
MD5: 72C35B7A44D9BE5FA7A0AB9300664A3A
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo IJS - Institut Jožef Stefan
Povzetek: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.
Ključne besede:agent-based modeling, online social interactions, information diffusion, network structure analysis, homophily, reddit discussion networks
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:15.01.2026
Datum sprejetja članka:26.03.2026
Datum objave:09.04.2026
Založnik:IEEE
Leto izida:2026
Št. strani:str. 52890-52810
Številčenje:Vol. 14
Izvor:ZDA
PID:20.500.12556/DiRROS-29228 Novo okno
UDK:004
ISSN pri članku:2169-3536
DOI:10.1109/ACCESS.2026.3679263 Novo okno
COBISS.SI-ID:276633091 Novo okno
Avtorske pravice:© 2026 The Authors.
Opomba:Nasl. z nasl. zaslona; Soavtorji: Miha Češnovar, Alenka Guček, Marko Grobelnik; Opis vira z dne 28. 4. 2026;
Datum objave v DiRROS:28.04.2026
Število ogledov:76
Število prenosov:36
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:IEEE access
Založnik:Institute of Electrical and Electronics Engineers
ISSN:2169-3536
COBISS.SI-ID:519839513 Novo okno

Gradivo je financirano iz projekta

Financer:EC - European Commission
Številka projekta:101095095
Naslov:TWin of Online Social Networks
Akronim:TWON

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:09.04.2026
Vezano na:VoR

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:agentno modeliranje, spletne družbene interakcije, širjenje informacij, analiza omrežne strukture, homofilija, omrežja razprav na Redditu


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