Special Issue "Information Diffusion in Social Networks"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".

Deadline for manuscript submissions: 28 March 2019

Special Issue Editor

Guest Editor
Prof. Paolo Pin

Department of Decision Sciences and IGIER, Università Bocconi, Via Roberto Sarfatti, 25, 20100 Milano, Italy
Website | E-Mail
Interests: game theory; social networks; complex networks

Special Issue Information

Dear Colleagues,

Studying social networks is the basis for understanding many complex phenomena in our societies.

When do social networks help the efficiency of economic and social activities, and when do they, instead, slow down the coordination and accruement of welfare? Do social networks provide a general informal answer to problems of integration and coexistence of different cultures, or do they increase polarization and segregation? The theory of complex networks has shown that the networks of human relations have statistical characteristics (as the so called ‘small world’ property) that accelerate the spread of opinions, but what if the behavior itself of people may either reduce this spread or instead incentivize the propagation of fake news? When is it the case that having wrong beliefs about reality does not only harm a single subject and his social neighbors, but may have cascade effects over a non-negligible portion of the overall society? In this respect, is the case of online social networks different from the case of real world acquaintances?

These are some of the questions at the core of this Special Issue.

Prof. Paolo Pin
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • social networks
  • information diffusion
  • opinions
  • echo chambers
  • polarization
  • fake news
  • online social networks

Published Papers (1 paper)

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Research

Open AccessArticle Exploring How Homophily and Accessibility Can Facilitate Polarization in Social Networks
Information 2018, 9(12), 325; https://doi.org/10.3390/info9120325
Received: 30 October 2018 / Revised: 1 December 2018 / Accepted: 11 December 2018 / Published: 14 December 2018
PDF Full-text (1465 KB) | HTML Full-text | XML Full-text
Abstract
Polarization in online social networks has gathered a significant amount of attention in the research community and in the public sphere due to stark disagreements with millions of participants on topics surrounding politics, climate, the economy and other areas where an agreement is
[...] Read more.
Polarization in online social networks has gathered a significant amount of attention in the research community and in the public sphere due to stark disagreements with millions of participants on topics surrounding politics, climate, the economy and other areas where an agreement is required. This work investigates into greater depth a type of model that can produce ideological segregation as a result of polarization depending on the strength of homophily and the ability of users to access similar minded individuals. Whether increased access can induce larger amounts of societal separation is important to investigate, and this work sheds further insight into the phenomenon. Center to the hypothesis of homophilic alignments in friendship generation is that of a discussion group or community. These are modeled and the investigation into their effect on the dynamics of polarization is presented. The social implications demonstrate that initial phases of an ideological exchange can result in increased polarization, although a consensus in the long run is expected and that the separation between groups is amplified when groups are constructed with ideological homophilic preferences. Full article
(This article belongs to the Special Issue Information Diffusion in Social Networks)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Exploding Mechanism and Governance of False Information in Public Crises
Authors: Xiaoxia Zhu 1,2, Jiaxin Song 1,  John Gershenson 2 and Jianfang Meng 1,*
Affiliations:
1 School of Economics and Management, Yanshan University, Qinghuangdao 066004, China
2 College of Engineering, The Pennsylvania State University, PA 16802, United States
Abstract: The sudden outbreak of the public crisis is often accompanied by the false information. The large-scale spread of false information will not only cause panic in the crowd, but it may also trigger a public crisis and cause secondary harm to the society,which puts forward higher demands on the government’s governance. Based on the theory of explosive percolation and combined with SI model, this paper proposes an improved false information dissemination model. Through the analysis of such indicators as the the largest cluster, explosive threshold, cluster merging and diffusion rate, explored the explosive mechanism of the emergence of false information. It is found that there is a threshold for the outbreak of the false information, and the outbreak size is almost zero when the threshold is smaller than the threshold. After the threshold is exceeded, the outbreak will occur rapidly in a short time. False information is most infective in the early stage, and gradually weakened with the increase of simulation steps. Based on this mechanism, this paper presents three kinds of false information governance options: random immunization, target-surrounded immunization, and comprehensive science. The rationality of different situations is verified through simulation experiments. Under the circumstance of frequent occurrence of false information and triggering of public crisis, It is of great significance to study the mechanism of its outbreak on the government intervention.

Title: Network Models of Information Diffusion Processes
Author:Tobias Hecking
Affiliation:University of Duisburg-Essen
Abstract:Network analysis is one of the main means for analysing information diffusion processes.
However, as the notion of an "information diffusion process" very much depends on the
application context, network models mapping those processes may differ very much.
Nodes can represent different entitites, for example, individuals, content items, or events. Apart
from the instantiation of nodes, an analyst also has to decide when and how to establish an edge
between them.
Furthermore, the strenght of network models to map structural characteristics often comes at a cost
of loosing temporal information about the underlying process since connections between nodes
are aggregated over time. In certain cases, however, information diffusion processes can be
captured in specific network models that bear an inherent notion of time.
This paper reviews and compares approaches of transforming data about information diffusion into
network structures with a special consideration of handling temporal information.
It will be shown by how modelling decisions affect the analysis of information diffusion using
network analysis techniques.

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