Relevant bibliographies by topics / Endogenous diffusion social networks

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Endogenous diffusion social networks'

Author: Grafiati
Published: 14 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Endogenous diffusion social networks"

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Pavan, Elena. "Embedding Digital Communications Within Collective Action Networks: A Multidimensional Network Approach." Mobilization: An International Quarterly 19, no. 4 (2014): 441–55. http://dx.doi.org/10.17813/maiq.19.4.w24rl524u074126k.

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In this article, we conceive of digital media as embedded within social networks, and use this perspective to examine the role of online communications in collective action. We claim that the adoption of this perspective requires two shifts: first, rethinking the ontological separation between media and social networks of action that has, so far, characterized research in this domain; second, the adoption of flexible tools that enable us to account, simultaneously, for the multiplicity of relations underpinning collective efforts and the hybrid interplay between direct and technology-mediated
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Chang, Myong‐Hun, and Joseph E. Harrington, Jr. "Discovery and Diffusion of Knowledge in an Endogenous Social Network." American Journal of Sociology 110, no. 4 (2005): 937–76. http://dx.doi.org/10.1086/426555.

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Goldberg, Amir, and Sarah K. Stein. "Beyond Social Contagion: Associative Diffusion and the Emergence of Cultural Variation." American Sociological Review 83, no. 5 (2018): 897–932. http://dx.doi.org/10.1177/0003122418797576.

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Network models of diffusion predominantly think about cultural variation as a product of social contagion. But culture does not spread like a virus. We propose an alternative explanation we call associative diffusion. Drawing on two insights from research in cognition—that meaning inheres in cognitive associations between concepts, and that perceived associations constrain people’s actions—we introduce a model in which, rather than beliefs or behaviors, the things being transmitted between individuals are perceptions about what beliefs or behaviors are compatible with one another. Conventional
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Koley, Paramita, Avirup Saha, Sourangshu Bhattacharya, Niloy Ganguly, and Abir De. "Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach." ACM Transactions on Knowledge Discovery from Data 15, no. 6 (2021): 1–25. http://dx.doi.org/10.1145/3449361.

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The networked opinion diffusion in online social networks is often governed by the two genres of opinions— endogenous opinions that are driven by the influence of social contacts among users, and exogenous opinions which are formed by external effects like news and feeds. Accurate demarcation of endogenous and exogenous messages offers an important cue to opinion modeling, thereby enhancing its predictive performance. In this article, we design a suite of unsupervised classification methods based on experimental design approaches, in which, we aim to select the subsets of events which minimize
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Wejnert, Barbara. "Diffusion, Development, and Democracy, 1800-1999." American Sociological Review 70, no. 1 (2005): 53–81. http://dx.doi.org/10.1177/000312240507000104.

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While a trend of growth in democratization over the past two centuries has been generally observed, it is the remarkable growth in the democratization of the world over the past 30 years that has truly captured the imagination of social scientists, policymakers, and the general public alike. Two major sets of factors have dominated studies attempting to predict democratization. One set characterizes endogenous or internal features of countries, and may be referred to as socioeconomic development. The other set, less often tested, characterizes exogenous variables that influence democratization
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Everall, Jordan P., Fabian Tschofenig, Jonathan F. Donges, and Ilona M. Otto. "The Pareto effect in tipping social networks: from minority to majority." Earth System Dynamics 16, no. 1 (2025): 189–214. https://doi.org/10.5194/esd-16-189-2025.

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Abstract. How do social networks tip? A popular theory is that a small minority can trigger population-wide social change. This aligns with the Pareto principle, a semi-quantitative law which suggests that, in many systems, 80 % of effects arise from 20 % of the causes. In the context of the transition to net-zero emissions, this vital 20 % can be a critical instigator of social tipping, a process which can rapidly change social norms. In this work, we asked whether the Pareto effect can be observed in social systems by conducting a literature review, placing a focus on social norm diffusion a
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Bartesaghi, Paolo, Gian Paolo Clemente, and Rosanna Grassi. "A Self-Adaptive Centrality Measure for Asset Correlation Networks." Economies 12, no. 7 (2024): 164. http://dx.doi.org/10.3390/economies12070164.

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We propose a new centrality measure based on a self-adaptive epidemic model characterized by an endogenous reinforcement mechanism in the transmission of information between nodes. We provide a strategy to assign to nodes a centrality score that depends, in an eigenvector centrality scheme, on that of all the elements of the network, nodes and edges, connected to it. We parameterize this score as a function of a reinforcement factor, which for the first time implements the intensity of the interaction between the network of nodes and that of the edges. In this proposal, a local centrality meas
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Huang, Hung-Chun, and Hsin-Yu Shih. "Exploring the structure of international technology diffusion." Foresight 16, no. 3 (2014): 210–28. http://dx.doi.org/10.1108/fs-11-2012-0085.

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Purpose – This paper aims to provide a macro perspective on diffusion structure research, and to investigate the deep structure of international technology diffusion and structural differences between technology diffusion networks. This work also provides an understanding of the nature of globalization. Globalization has highlighted changes in socioeconomics and is reshaping the world. However, when comparing endogenous factors, exogenous factors are complex and demonstrate themselves as network phenomena. These network phenomena compose themselves as neither sole nor independent units. Countr
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Ioannidis, Evangelos, Nikos Varsakelis, and Ioannis Antoniou. "Promoters versus Adversaries of Change: Agent-Based Modeling of Organizational Conflict in Co-Evolving Networks." Mathematics 8, no. 12 (2020): 2235. http://dx.doi.org/10.3390/math8122235.

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The social adoption of change is usually hard because in reality, forces opposing the social adoption of change manifest. This situation of organizational conflict corresponds to the case where two competing groups of influential agents (“promoters” versus “adversaries” of change) operate concurrently within the same organizational network. We model and explore the co-evolution of interpersonal ties and attitudes in the presence of conflict, taking into account explicitly the microscopic “agent-to-agent” interactions. In this perspective, we propose a new ties-attitudes co-evolution model wher
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Hojman, Daniel A., and Adam Szeidl. "Endogenous networks, social games, and evolution." Games and Economic Behavior 55, no. 1 (2006): 112–30. http://dx.doi.org/10.1016/j.geb.2005.02.007.

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Dissertations / Theses on the topic "Endogenous diffusion social networks"

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MUSCILLO, ALESSIO. "Endogenous Diffusion in Social Networks. Two Cases: Infectious Diseases and Sharing of Knowledge." Doctoral thesis, Università di Siena, 2017. http://hdl.handle.net/11365/1059090.

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Complex phenomena arising from the interaction of ``elemental'' pieces have been first studied in physics and biology, where such constitutive particles were given deterministic rules for their behavior. In that context it was already clear that even critical outcomes can result on the aggregate level in situations where agents' behaviors are ``mechanic'' and ``simple''. In recent years, inspired by real-world phenomena, economics and other social sciences have also started to play a role in this very wide strand of research. On the one hand, by introducing degrees of rationality in agents
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Bimpikis, Kostas. "Strategic delay and information exchange in endogenous social networks." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62405.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2010.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 160-165).<br>This thesis studies optimal stopping problems for strategic agents in the context of two economic applications: experimentation in a competitive market and information exchange in social networks. The economic agents (firms in the first application, individuals in the second) take actions, whose payoffs depend on an unknown underlying state. Our framework is characterized by the fol
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Pedersen, Tavis Joseph. "Tracking infection diffusion in social networks." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62557.

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This thesis explores the problem of tracking the diffusion of contagion processes on social networks. Infection (or Information) diffusion is modeled using the Susceptible-Infected-Susceptible (SIS) model. Mean field approximation is employed to approximate the discrete valued infection dynamics by a deterministic ordinary differential equation, thereby yielding a generative model for the infection diffusion. The infection is shown to follow polynomial dynamics and is estimated using an exact non-linear Bayesian filter. We compute posterior Cramer-Rao bounds to obtain the fundamental limits of
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Sun, Hongxian, and 孙鸿賢. "Modeling information diffusion in social networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48330127.

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Interpersonal communication with network infrastructure creates mobile and online social networks, which shorten the distance among people. It naturally leads to an important question asking for a clear and detailed description of information dissemination and diffusion process in social networks. An in-depth understanding of the question may help in various aspects,e.g., designing better communication protocols and predicting the demand of hot contents. In the thesis we focus on two concrete sub-questions. The first one is to describe the performance of mobile social networks under the pr
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DE, NICOLA ANTONIO. "Diffusion of interests in social networks." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2015. http://hdl.handle.net/2108/202331.

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This thesis provides a model for diusion of interests in Social Networks (SNs). It demonstrates that the topology of the SN plays a crucial role in the dynamics of the individual interests. Understanding cultural phenomena on SNs and exploiting the implicit knowledge about their members is attracting the interest of dierent research communities both from the academic and the business side. The community of complexity science is devoting signicant eorts to dene laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a produ
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Yang, Yile, and 楊頤樂. "Noncooperative information diffusion in online social networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206693.

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Information diffusion in online social networks has received attention in both research and actual applications. The prevalence of online social networking sites offers the possibility of mining for necessary information. However, existing influence maximization algorithms and newly proposed influence diffusion models do not distinguish between seed nodes (or pilot users) and nonseed nodes and assume all nodes are cooperative in propagating influence. This thesis investigates models and heuristics for noncooperative information diffusion in online social networks. It consists of three parts: t
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Marchenko, Maria. "Endogenous Shocks in Social Networks: Exam Failures and Friends' Future Performance." WU Vienna University of Economics and Business, 2019. http://epub.wu.ac.at/7100/1/wp292.pdf.

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Exam failures of the students in a specific network may influence not only the future performance of the student but also all students from their friendship networks, affecting the overall cohort's performance. Therefore, it is crucial to understand how the whole network responses to failure. The difficulty of such analysis is incorporated in the probability of the failures being highly endogenous. In this paper, I am applying the novel identification and estimation approach to deal with such endogeneity. I am exploring the dynamic data on the students' networks in HSE, Nizhniy Novgorod. The r
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Alemayehu, Atsede Ghidey <1986&gt. "Essays on social networks, altruism and information diffusion." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amsdottorato.unibo.it/9873/1/Atsede%20Ghidey%20Alemayehu_PhD%20Dissertation%282021%29%20Social%20Networks%20Altruism%20and%20Information%20Diffusion-final%20version.pdf.

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This dissertation consists of three standalone articles that contribute to the economics literature concerning technology adoption, information diffusion, and network economics in one way or another, using a couple of primary data sources from Ethiopia. The first empirical paper identifies the main behavioral factors affecting the adoption of brand new (radical) and upgraded (incremental) bioenergy innovations in Ethiopia. The results highlight the importance of targeting different instruments to increase the adoption rate of the two types of innovations. The second and the third empi
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Louzada, Pinto Julio Cesar. "Information diffusion and opinion dynamics in social networks." Thesis, Evry, Institut national des télécommunications, 2016. http://www.theses.fr/2016TELE0001/document.

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La dissémination d'information explore les chemins pris par l'information qui est transmise dans un réseau social, afin de comprendre et modéliser les relations entre les utilisateurs de ce réseau, ce qui permet une meilleur compréhension des relations humaines et leurs dynamique. Même si la priorité de ce travail soit théorique, en envisageant des aspects psychologiques et sociologiques des réseaux sociaux, les modèles de dissémination d'information sont aussi à la base de plusieurs applications concrètes, comme la maximisation d'influence, la prédication de liens, la découverte des noeuds in
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Louzada, Pinto Julio Cesar. "Information diffusion and opinion dynamics in social networks." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2016. http://www.theses.fr/2016TELE0001.

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La dissémination d'information explore les chemins pris par l'information qui est transmise dans un réseau social, afin de comprendre et modéliser les relations entre les utilisateurs de ce réseau, ce qui permet une meilleur compréhension des relations humaines et leurs dynamique. Même si la priorité de ce travail soit théorique, en envisageant des aspects psychologiques et sociologiques des réseaux sociaux, les modèles de dissémination d'information sont aussi à la base de plusieurs applications concrètes, comme la maximisation d'influence, la prédication de liens, la découverte des noeuds in
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Books on the topic "Endogenous diffusion social networks"

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Shakarian, Paulo, Abhivav Bhatnagar, Ashkan Aleali, Elham Shaabani, and Ruocheng Guo. Diffusion in Social Networks. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23105-1.

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Klochko, Marianna A. Endogenous time preferences in social networks. Edward Elgar Pub., 2005.

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1942-, Ordeshook Peter C., ed. Endogenous time preferences in social networks. Edward Elgar Pub., 2006.

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Acemoglu, Daron. Dynamics of information exchange in endogenous social networks. National Bureau of Economic Research, 2010.

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Acemoglu, Daron. Dynamics of information exchange in endogenous social networks. National Bureau of Economic Research, 2010.

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Windzio, Michael, Ivo Mossig, Fabian Besche-Truthe, and Helen Seitzer, eds. Networks and Geographies of Global Social Policy Diffusion. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83403-6.

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1965-, Coutard Olivier, Hanley Richard, and Zimmerman Rae, eds. Sustaining urban networks: The social diffusion of large technical systems. Routledge, 2004.

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Wang, Haiyan, Feng Wang, and Kuai Xu. Modeling Information Diffusion in Online Social Networks with Partial Differential Equations. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38852-2.

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Robalino, David A. Social capital, technology diffusion, and sustainable growth in the developing world. RAND, 2000.

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Galagedarage, Madhubhashini. Digital divide: Internet diffusion in Sri Lanka. S. Godage & Brothers (Pvt) Ltd, 2017.

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Book chapters on the topic "Endogenous diffusion social networks"

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Aggrawal, Niyati, and Adarsh Anand. "Information Diffusion." In Social Networks. CRC Press, 2022. http://dx.doi.org/10.1201/9781003088066-10.

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Wu, Jiang. "Diffusion in Social Networks." In Social Network Computing. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4084-0_10.

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Duggan, Jim. "Diffusion Models." In Lecture Notes in Social Networks. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-34043-2_5.

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Louni, Alireza, and K. P. Subbalakshmi. "Diffusion of Information in Social Networks." In Social Networking. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05164-2_1.

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Immorlica, Nicole. "Technology Diffusion in Social Networks." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-95891-8_5.

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Etesami, Seyed Rasoul. "Diffusion Games over Social Networks." In Potential-Based Analysis of Social, Communication, and Distributed Networks. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54289-8_7.

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Xu, Wen, Weili Wu, Lidan Fan, Zaixin Lu, and Ding-Zhu Du. "Influence Diffusion in Social Networks." In Optimization in Science and Engineering. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0808-0_27.

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Al-Taie, Mohammed Zuhair, and Seifedine Kadry. "Information Diffusion in Social Networks." In Advanced Information and Knowledge Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53004-8_8.

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Valente, Thomas W. "Social Networks, Diffusion Processes in." In Computational Complexity. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-1800-9_181.

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Valente, Thomas W. "Social Networks, Diffusion Processes in." In Encyclopedia of Complexity and Systems Science. Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-30440-3_493.

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Conference papers on the topic "Endogenous diffusion social networks"

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De, Abir, Sourangshu Bhattacharya, and Niloy Ganguly. "Demarcating Endogenous and Exogenous Opinion Diffusion Process on Social Networks." In the 2018 World Wide Web Conference. ACM Press, 2018. http://dx.doi.org/10.1145/3178876.3186121.

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Bimpikis, Kostas, Daron Acemoglu, and Asuman Ozdaglar. "Communication dynamics in endogenous social networks." In the Behavioral and Quantitative Game Theory. ACM Press, 2010. http://dx.doi.org/10.1145/1807406.1807499.

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Tatara, Eric, Nicholson Collier, Jonathan Ozik, and Charles Macal. "Endogenous Social Networks from Large-Scale Agent-Based Models." In 2017 IEEE International Parallel and Distributed Processing Symposium: Workshops (IPDPSW). IEEE, 2017. http://dx.doi.org/10.1109/ipdpsw.2017.83.

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Chanhyun Kang, C. Molinaro, S. Kraus, Y. Shavitt, and V. S. Subrahmanian. "Diffusion Centrality in Social Networks." In 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012). IEEE, 2012. http://dx.doi.org/10.1109/asonam.2012.95.

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Agrawal, Divyakant, Ceren Budak, and Amr El Abbadi. "Information diffusion in social networks." In the 20th ACM international conference. ACM Press, 2011. http://dx.doi.org/10.1145/2063576.2064036.

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Neves, Felipe, Victor Ströele, and Fernanda Campos. "Information Diffusion in Social Networks." In SBSI'19: XV Brazilian Symposium on Information Systems. ACM, 2019. http://dx.doi.org/10.1145/3330204.3330234.

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Mehdiabadi, Motahareh Eslami, Hamid R. Rabiee, and Mostafa Salehi. "Sampling from Diffusion Networks." In 2012 International Conference on Social Informatics (SocialInformatics). IEEE, 2012. http://dx.doi.org/10.1109/socialinformatics.2012.79.

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Balali, Ali, Aboozar Rajabi, Sepehr Ghassemi, Masoud Asadpour, and Hesham Faili. "Content diffusion prediction in social networks." In 2013 5th Conference on Information and Knowledge Technology (IKT). IEEE, 2013. http://dx.doi.org/10.1109/ikt.2013.6620114.

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Gayraud, Nathalie T. H., Evaggelia Pitoura, and Panayiotis Tsaparas. "Diffusion Maximization in Evolving Social Networks." In COSN'15: Conference on Online Social Networks. ACM, 2015. http://dx.doi.org/10.1145/2817946.2817965.

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Amato, Flora, Vincenzo Moscato, Antonio Picariello, and Giancarlo Sperlí. "Diffusion Algorithms in Multimedia Social Networks." In ASONAM '17: Advances in Social Networks Analysis and Mining 2017. ACM, 2017. http://dx.doi.org/10.1145/3110025.3116207.

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Reports on the topic "Endogenous diffusion social networks"

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Acemoglu, Daron, Kostas Bimpikis, and Asuman Ozdaglar. Dynamics of Information Exchange in Endogenous Social Networks. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w16410.

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Montgomery, Mark, and John Casterline. Social networks and the diffusion of fertility control. Population Council, 1998. http://dx.doi.org/10.31899/pgy6.1020.

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Hirshleifer, David, Lin Peng, and Qiguang Wang. News Diffusion in Social Networks and Stock Market Reactions. National Bureau of Economic Research, 2023. http://dx.doi.org/10.3386/w30860.

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Fafchamps, Marcel, Asadul Islam, Debayan Pakrashi, and Denni Tommasi. Diffusion in Social Networks: Experimental Evidence on Information Sharing vs Persuasion. National Bureau of Economic Research, 2024. https://doi.org/10.3386/w33285.

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Halberstam, Yosh, and Brian Knight. Homophily, Group Size, and the Diffusion of Political Information in Social Networks: Evidence from Twitter. National Bureau of Economic Research, 2014. http://dx.doi.org/10.3386/w20681.

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Rose, Erin M., and Beth A. Hawkins. Assessing the Potential of Social Networks as a Means for Information Diffusion the Weatherization Experiences (WE) Project. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1354643.

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Dillon, Andrew, Deanna Olney, Marie Ruel, et al. The diffusion of health knowledge through social networks: An impact evaluation of health knowledge asymmetries on child health in Burkina Faso. International Initiative for Impact Evaluation, 2014. http://dx.doi.org/10.23846/ow2170.

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Pietrobelli, Carlo, and Elisa Giuliani. Social Network Analysis Methodologies for the Evaluation of Cluster Development Programs. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0008963.

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Cluster development programs (CDPs) have been adopted widely in many countries worldwide. Many such programs aim to promote economic development by forming and strengthening inter-organizational networks. Despite their widespread diffusion, we know very little about CDP outputs or the impact CDPs have on host regions and their populations. Evaluation studies are beginning to appear, but the overall concern is that a distinct evaluation concept and method with a focus on CDPs is not yet available. The objective of this paper is to address this limitation, by proposing a novel methodological app
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Behrman, Jere R., Hans-Peter Kohler, and Susan Cotts Watkins. How can we measure the causal effects of social networks using observational data? Evidence from the diffusion of family planning and AIDS worries in South Nyanza District, Kenya. Max Planck Institute for Demographic Research, 2001. http://dx.doi.org/10.4054/mpidr-wp-2001-022.

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