Community detection inside networks represents an area which has gained a paramount importance in the last decade.

    With the massive spreading of online communications several attempts have been performed to investigate correlations between the “Real world” and social networks, both in terms number of connections between people and consistency of relationship. This research delves into the relations occurred on Facebook and Twitter which can be used as a proxy for the relations in offline social networks, such as networks of human face-to-face (F2F) proximity.

    The final aim is focused on discovering the most meaningful patterns that rule the hierarchy of bonds by means of the comparison of several algorithms widely recognized as effective for different applications, such a routing, link prediction, crimes and recently containment of virus outbreak.


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    Titel :

    Multidimensional Network Analysis to Predict Correlations Between Offline and Online Interactions


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wang, Yi (Herausgeber:in) / Martinsen, Kristian (Herausgeber:in) / Yu, Tao (Herausgeber:in) / Wang, Kesheng (Herausgeber:in) / Chirici, Lapo (Autor:in) / Parotti, Francesca (Autor:in) / Wang, Yi (Autor:in)

    Kongress:

    International Workshop of Advanced Manufacturing and Automation ; 2020 ; Zhanjiang, China October 12, 2020 - October 13, 2020



    Erscheinungsdatum :

    2021-01-23


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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