feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    UID:
    almafu_BV045099552
    Format: 1 Online-Ressource (VI, 361 p. 104 illus., 81 illus. in color).
    ISBN: 978-3-319-77332-2
    Series Statement: Computational Social Sciences
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-77331-5
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Information ; Verbreitung ; Soziales System ; Aufsatzsammlung ; Aufsatzsammlung ; Aufsatzsammlung
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    UID:
    edochu_18452_27881
    Format: 1 Online-Ressource (24 Seiten)
    ISSN: 1951-6355 , 1951-6355
    Content: Spreading dynamics and complex contagion processes on networks are important mechanisms underlying the emergence of critical transitions, tipping points and other non-linear phenomena in complex human and natural systems. Increasing amounts of temporal network data are now becoming available to study such spreading processes of behaviours, opinions, ideas, diseases and innovations to test hypotheses regarding their specific properties. To this end, we here present a methodology based on dose–response functions and hypothesis testing using surrogate data models that randomise most aspects of the empirical data while conserving certain structures relevant to contagion, group or homophily dynamics. We demonstrate this methodology for synthetic temporal network data of spreading processes generated by the adaptive voter model. Furthermore, we apply it to empirical temporal network data from the Copenhagen Networks Study. This data set provides a physically-close-contact network between several hundreds of university students participating in the study over the course of 3 months. We study the potential spreading dynamics of the health-related behaviour “regularly going to the fitness studio” on this network. Based on a hierarchy of surrogate data models, we find that our method neither provides significant evidence for an influence of a dose–response-type network spreading process in this data set, nor significant evidence for homophily. The empirical dynamics in exercise behaviour are likely better described by individual features such as the disposition towards the behaviour, and the persistence to maintain it, as well as external influences affecting the whole group, and the non-trivial network structure. The proposed methodology is generic and promising also for applications to other temporal network data sets and traits of interest.
    Content: Peer Reviewed
    In: Heidelberg : Springer, 230,16-17, Seiten 3311-3334, 1951-6355
    Language: English
    URL: Volltext  (kostenfrei)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    UID:
    kobvindex_GFZ1026857589
    Format: VI, 361 Seiten , Illustrationen, Diagramme
    ISBN: 9783319773315 , 9783319773322
    Series Statement: Computational Social Sciences
    Note: Contents: Part 1: Introduction to Spreading in Social Systems ; Complex Contagions: A Decade in Review ; A Simple Person’s Approach to Understanding the Contagion Condition for Spreading Processes on Generalized Random Networks ; Challenges to Estimating Contagion Effects from Observational Data ; Part 2: Models and Theories ; Slightly Generalized Contagion: Unifying Simple Models of Biological and Social Spreading ; Message-Passing Methods for Complex Contagions ; Optimal Modularity in Complex Contagion ; Probing Empirical Contact Networks by Simulation of Spreading Dynamics ; Theories for Influencer Identification in Complex Networks ; Part 3: Observational Studies ; Service Adoption Spreading in Online Social Networks ; Misinformation Spreading on Facebook ; Scalable Detection of Viral Memes from Diffusion Patterns ; Attention on Weak Ties in Social and Communication Networks ; Measuring Social Spam and the Effect of Bots on Information Diffusion in Social Media ; Network Happiness: How Online Social Interactions Relate to Our Well Being ; Information Spreading During Emergencies and Anomalous Events ; Part 4: Controlled Studies ; Randomized Experiments to Detect and Estimate Social Influence in Networks ; The Rippling Effect of Social Influence via Phone Communication Network ; Network Experiments Through Academic-Industry Collaboration ; Spreading in Social Systems: Reflections
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages