Literature DB >> 23419847

Analysis of large-scale social and information networks.

Jon Kleinberg1.   

Abstract

The growth of the Web has required us to think about the design of information systems in which large-scale computational and social feedback effects are simultaneously at work. At the same time, the data generated by Web-scale systems--recording the ways in which millions of participants create content, link information, form groups and communicate with one another--have made it possible to evaluate long-standing theories of social interaction, and to formulate new theories based on what we observe. These developments have created a new level of interaction between computing and the social sciences, enriching the perspectives of both of these disciplines. We discuss some of the observations, theories and conclusions that have grown from the study of Web-scale social interaction, focusing on issues including the mechanisms by which people join groups, the ways in which different groups are linked together in social networks and the interplay of positive and negative interactions in these networks.

Entities:  

Year:  2013        PMID: 23419847     DOI: 10.1098/rsta.2012.0378

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  6 in total

1.  Web science: a new frontier.

Authors:  Nigel Shadbolt; Wendy Hall; James A Hendler; William H Dutton
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2013-02-18       Impact factor: 4.226

2.  Trend of Narratives in the Age of Misinformation.

Authors:  Alessandro Bessi; Fabiana Zollo; Michela Del Vicario; Antonio Scala; Guido Caldarelli; Walter Quattrociocchi
Journal:  PLoS One       Date:  2015-08-14       Impact factor: 3.240

3.  Science vs conspiracy: collective narratives in the age of misinformation.

Authors:  Alessandro Bessi; Mauro Coletto; George Alexandru Davidescu; Antonio Scala; Guido Caldarelli; Walter Quattrociocchi
Journal:  PLoS One       Date:  2015-02-23       Impact factor: 3.240

4.  Link Prediction in Weighted Networks: A Weighted Mutual Information Model.

Authors:  Boyao Zhu; Yongxiang Xia
Journal:  PLoS One       Date:  2016-02-05       Impact factor: 3.240

5.  Leaking privacy and shadow profiles in online social networks.

Authors:  David Garcia
Journal:  Sci Adv       Date:  2017-08-04       Impact factor: 14.136

6.  Link prediction in complex networks: a mutual information perspective.

Authors:  Fei Tan; Yongxiang Xia; Boyao Zhu
Journal:  PLoS One       Date:  2014-09-10       Impact factor: 3.240

  6 in total

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