LEADER 02875nam 22005655 450 001 9911049108603321 005 20260102122812.0 010 $a3-032-10130-1 024 7 $a10.1007/978-3-032-10130-3 035 $a(CKB)44769975400041 035 $a(MiAaPQ)EBC32470859 035 $a(Au-PeEL)EBL32470859 035 $a(DE-He213)978-3-032-10130-3 035 $a(EXLCZ)9944769975400041 100 $a20260102d2026 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Infodemiology $eBelief System Mapping and Social Stress /$fby Herkulaas Combrink 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (94 pages) 225 1 $aSpringerBriefs in Computer Science,$x2191-5776 311 08$a3-032-10129-8 327 $aPreface -- Chapter 1 Introduction to Computational Infodemiology -- Chapter 2 Agent Based Modelling and Reinforcement Learning in Computational Infodemiology -- Chapter 3 A Framework for Modelling Belief Systems -- Chapter 4 Modelling Belief Systems -- Chapter 5 Social Stress Indicators. 330 $aComputational Infodemiology is a novel discipline that maps the indicators that underpin digital discourse. Being able to fundamentally map belief systems within a scale free network and provide a framework by which the evolution of belief can be mapped, outlines the impact uncertainty has on an echo chamber and models the spread of misinformation. This book provides the framework and empirical data to outline these scenarios. To map the impact of uncertainty, certain indicators need to be tracked, and within the scale-free network, social stress indicators are introduced. These social stress indicators serve as a proxy for potential harm and can differentiate between low, medium and high levels of harm. By incorporating social stress indicators, belief system mapping becomes viable and possible to model misinformation spread within an echo chamber. 410 0$aSpringerBriefs in Computer Science,$x2191-5776 606 $aArtificial intelligence 606 $aMachine learning 606 $aMass media$xMoral and ethical aspects 606 $aArtificial Intelligence 606 $aMachine Learning 606 $aMedia Ethics 615 0$aArtificial intelligence. 615 0$aMachine learning. 615 0$aMass media$xMoral and ethical aspects. 615 14$aArtificial Intelligence. 615 24$aMachine Learning. 615 24$aMedia Ethics. 676 $a006.3 700 $aCombrink$b Herkulaas$01885325 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911049108603321 996 $aComputational Infodemiology$94520522 997 $aUNINA