標(biāo)題: Titlebook: Complex Spreading Phenomena in Social Systems; Influence and Contag Sune Lehmann,Yong-Yeol Ahn Book 2018 Springer International Publishing [打印本頁] 作者: papertrans 時(shí)間: 2025-3-21 17:50
書目名稱Complex Spreading Phenomena in Social Systems影響因子(影響力)
書目名稱Complex Spreading Phenomena in Social Systems影響因子(影響力)學(xué)科排名
書目名稱Complex Spreading Phenomena in Social Systems網(wǎng)絡(luò)公開度
書目名稱Complex Spreading Phenomena in Social Systems網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Complex Spreading Phenomena in Social Systems被引頻次
書目名稱Complex Spreading Phenomena in Social Systems被引頻次學(xué)科排名
書目名稱Complex Spreading Phenomena in Social Systems年度引用
書目名稱Complex Spreading Phenomena in Social Systems年度引用學(xué)科排名
書目名稱Complex Spreading Phenomena in Social Systems讀者反饋
書目名稱Complex Spreading Phenomena in Social Systems讀者反饋學(xué)科排名
作者: granite 時(shí)間: 2025-3-21 21:50
A Simple Person’s Approach to Understanding the Contagion Condition for Spreading Processes on Genernetworks. We show how the contagion condition can be broken into three elements, two structural in nature, and the third a meshing of the contagion process and the network. The contagion conditions we obtain reflect the spreading dynamics in a clear, interpretable way. For threshold contagion, we di作者: corporate 時(shí)間: 2025-3-22 02:42
Slightly Generalized Contagion: Unifying Simple Models of Biological and Social Spreadingion. Generalized contagion builds on the elementary observation that spreading and contagion of all kinds involve some form of system memory. We discuss the three main classes of systems that generalized contagion affords, resembling: simple biological contagion; critical mass contagion of social ph作者: 衍生 時(shí)間: 2025-3-22 08:39 作者: 全能 時(shí)間: 2025-3-22 08:58 作者: 使更活躍 時(shí)間: 2025-3-22 14:09
Probing Empirical Contact Networks by Simulation of Spreading Dynamics of the spreading processes. By investigating these relationships one gains understanding both of the spreading itself and the structure and function of the contact network. In this chapter, we will summarize the recent literature using simulation of spreading processes on top of empirical contact d作者: 使更活躍 時(shí)間: 2025-3-22 20:22 作者: Brain-Imaging 時(shí)間: 2025-3-22 22:23
Service Adoption Spreading in Online Social Networksfabric of society. This process is arguably driven by social influence, social learning and by external effects like media. Observations of such processes date back to the seminal studies by Rogers and Bass, and their mathematical modelling has taken two directions: One paradigm, called simple conta作者: surmount 時(shí)間: 2025-3-23 01:52 作者: 有發(fā)明天才 時(shí)間: 2025-3-23 08:07 作者: 態(tài)學(xué) 時(shí)間: 2025-3-23 13:13 作者: Cytology 時(shí)間: 2025-3-23 16:52 作者: Migratory 時(shí)間: 2025-3-23 18:28
Network Happiness: How Online Social Interactions Relate to Our Well Beingast decade has allowed us to study human social behavior at a previously unimaginable scale and level of detail through the availability of extensive detailed social records for billions of individuals. In this chapter we review several recent results on the structure of the social networks of which作者: Digest 時(shí)間: 2025-3-23 23:17
Information Spreading During Emergencies and Anomalous Eventsons can now turn to an array of communication channels, from mobile phone calls and text messages to social media posts, when alerting social ties. These channels drastically improve the speed of information in a time-sensitive event, and provide extant records of human dynamics during and afterward作者: 擁護(hù) 時(shí)間: 2025-3-24 04:42 作者: LEER 時(shí)間: 2025-3-24 06:48
Book 2018ften using randomized control trials to isolate the network effect from confounders, such as homophily...Each contribution is authored by leading experts in the field. This volume, though based on technical selections of the most important results on complex spreading, remains quite accessible to th作者: 淺灘 時(shí)間: 2025-3-24 13:44 作者: deadlock 時(shí)間: 2025-3-24 17:44 作者: 清真寺 時(shí)間: 2025-3-24 20:37 作者: labile 時(shí)間: 2025-3-24 23:43
Misinformation Spreading on Facebookroll contents, and (3) dissenting information e.g., debunking attempts. Our findings suggest that users tend to (a) join polarized communities sharing a common narrative (.), (b) acquire information confirming their beliefs (.) even if containing false claims, and (c) ignore dissenting information.作者: cognizant 時(shí)間: 2025-3-25 03:58
Attention on Weak Ties in Social and Communication Networkst attention, measured as the fraction of interactions devoted to a particular social connection, is high on weak ties—possibly reflecting the postulated informational purposes of such ties—but also on very strong ties. Data from online social media and mobile communication reveal network-dependent m作者: nurture 時(shí)間: 2025-3-25 09:57 作者: Vasoconstrictor 時(shí)間: 2025-3-25 12:15
Challenges to Estimating Contagion Effects from Observational Data作者: 繁榮地區(qū) 時(shí)間: 2025-3-25 15:48
https://doi.org/10.1007/978-3-8349-9649-7dy of how the structure of thresholds and their behavioral consequences can vary by individual and social context. The third area concerns the roles of diversity and homophily in the dynamics of complex contagion, including both diversity of demographic profiles among local peers and the broader not作者: 有權(quán) 時(shí)間: 2025-3-25 22:39
https://doi.org/10.1007/978-3-8349-9649-7ted. Finally, we present some applications of influencer identification in diverse real-world systems, including online social platforms, scientific publication, brain networks, and socioeconomic systems.作者: NOVA 時(shí)間: 2025-3-26 00:59
https://doi.org/10.1007/978-3-8349-9649-7ultaneous study of network structures and dynamics of online service adoption, shedding light on the mechanisms and external effects that influence the temporal evolution of behavioural or innovation adoption. These advancements have induced the development of more realistic models of social spreadi作者: 千篇一律 時(shí)間: 2025-3-26 08:09 作者: nullify 時(shí)間: 2025-3-26 10:39
Don Passey,Gavin Hawkins,Darren Cliftt attention, measured as the fraction of interactions devoted to a particular social connection, is high on weak ties—possibly reflecting the postulated informational purposes of such ties—but also on very strong ties. Data from online social media and mobile communication reveal network-dependent m作者: 愉快嗎 時(shí)間: 2025-3-26 13:15
Inger Langseth,Halvdan HaugsbakkenSubjective Well Being or happiness that is derived from a longitudinal sentiment analysis of the content written by each user over an extended period of time. We find that such Happiness is correlated with Popularity within social networks resulting in a so-called Happiness Paradox. In other words, 作者: single 時(shí)間: 2025-3-26 16:59 作者: 整理 時(shí)間: 2025-3-26 21:00
https://doi.org/10.1007/978-3-8349-9649-7networks. We show how the contagion condition can be broken into three elements, two structural in nature, and the third a meshing of the contagion process and the network. The contagion conditions we obtain reflect the spreading dynamics in a clear, interpretable way. For threshold contagion, we di作者: encomiast 時(shí)間: 2025-3-27 03:03 作者: custody 時(shí)間: 2025-3-27 05:37 作者: Meager 時(shí)間: 2025-3-27 13:10
https://doi.org/10.1007/978-3-8349-9649-7s the spreading of complex contagion. In particular, we focus on the notion of ., that predicts the occurrence of global cascades when the network exhibits just the right amount of modularity. Here we generalize the findings by assuming the presence of multiple communities and a uniform distribution作者: 淡紫色花 時(shí)間: 2025-3-27 14:06 作者: conformity 時(shí)間: 2025-3-27 21:37 作者: ERUPT 時(shí)間: 2025-3-27 22:16 作者: 繞著哥哥問 時(shí)間: 2025-3-28 03:35
https://doi.org/10.1007/978-3-8349-9649-7ce of a heterogeneous mass of information sources may affect the mechanisms behind the formation of public opinion. Such a scenario is a florid environment for digital wildfires when combined with functional illiteracy, information overload, and confirmation bias. In this essay, we focus on a collec作者: Immobilize 時(shí)間: 2025-3-28 08:52 作者: 飛行員 時(shí)間: 2025-3-28 11:33
Don Passey,Gavin Hawkins,Darren Cliftrity of interaction events; the second maintains that weak social ties, although less active, are often relevant for the exchange of especially important information (e.g., about potential new jobs in Granovetter’s work). While several empirical studies have provided support for the first hypothesis作者: gene-therapy 時(shí)間: 2025-3-28 16:42
Don Passey,Gavin Hawkins,Darren Clifthe social media human population. In this chapter, we will discuss the role of social bots in content spreading dynamics in social media. In particular, we will first investigate some differences between diffusion dynamics of content generated by bots, as opposed to humans, in the context of politic作者: ALT 時(shí)間: 2025-3-28 20:44 作者: Ballerina 時(shí)間: 2025-3-29 02:10
Don Passey,Gavin Hawkins,Darren Cliftons can now turn to an array of communication channels, from mobile phone calls and text messages to social media posts, when alerting social ties. These channels drastically improve the speed of information in a time-sensitive event, and provide extant records of human dynamics during and afterward作者: 打擊 時(shí)間: 2025-3-29 05:38
https://doi.org/10.1007/978-3-319-77332-2influence spreading; complex contagion; spreading in social systems; epidemic and social spreading; spre作者: FOR 時(shí)間: 2025-3-29 07:57 作者: CLOT 時(shí)間: 2025-3-29 12:45
Sune Lehmann,Yong-Yeol AhnContains for the first time in a single volume, chapters that take the reader from novice to expert on spreading processes in social systems.Uniquely emphasizes a data-driven approach to the problem o作者: 壓碎 時(shí)間: 2025-3-29 17:48
Computational Social Scienceshttp://image.papertrans.cn/c/image/231541.jpg作者: 冒號(hào) 時(shí)間: 2025-3-29 23:13
Complex Spreading Phenomena in Social Systems978-3-319-77332-2Series ISSN 2509-9574 Series E-ISSN 2509-9582 作者: largesse 時(shí)間: 2025-3-30 02:55
Nicholas Mavengere,Mikko Ruohonenures based on community structure even at the massive scales that common social media services need to process. Our results may not only enable practitioners to make predictions about meme diffusion, but also help researchers understand how and why different factors, in particular diffusion patterns in communities, affect online virality.作者: 使入迷 時(shí)間: 2025-3-30 04:18 作者: mosque 時(shí)間: 2025-3-30 09:33 作者: 預(yù)防注射 時(shí)間: 2025-3-30 15:34
