scholarly journals Locating multiple information sources in social networks based on the naming game

2020 ◽  
Vol 384 (35) ◽  
pp. 126908
Author(s):  
Xue Yang ◽  
Zhiliang Zhu ◽  
Hai Yu ◽  
Yuli Zhao ◽  
Ying Wang
Keyword(s):  
Social Networks ◽  
Information Sources ◽  
Naming Game

scholarly journals Point-of-Interest Recommender Systems based on Location-Based Social Networks: A Survey from an Experimental Perspective

2022 ◽  
Author(s):  
Pablo Sánchez ◽  
Alejandro Bellogín
Keyword(s):  
Social Networks ◽  
Recommender Systems ◽  
Information Sources ◽  
Learning Approaches ◽  
Performance Improvements ◽  
Point Of Interest ◽  
Real Performance ◽  
Research Questions ◽  
Developing Area ◽  
Location Based Social Networks

Point-of-Interest recommendation is an increasing research and developing area within the widely adopted technologies known as Recommender Systems. Among them, those that exploit information coming from Location-Based Social Networks (LBSNs) are very popular nowadays and could work with different information sources, which pose several challenges and research questions to the community as a whole. We present a systematic review focused on the research done in the last 10 years about this topic. We discuss and categorize the algorithms and evaluation methodologies used in these works and point out the opportunities and challenges that remain open in the field. More specifically, we report the leading recommendation techniques and information sources that have been exploited more often (such as the geographical signal and deep learning approaches) while we also alert about the lack of reproducibility in the field that may hinder real performance improvements.

A SOA-Based System for Territory Monitoring

2011 ◽  
pp. 426-454 ◽  
Author(s):  
Elena Roglia ◽  
Rosa Meo
Keyword(s):  
Social Networks ◽  
Web Services ◽  
System Architecture ◽  
Information Sources ◽  
Streaming Video ◽  
Tactical Planning ◽  
Spatial Objects ◽  
The Social ◽  
On Line ◽  
The Web

Next is a presentation of the complete system architecture, followed by a discussion of the details of the various services. Amongst these services, management and simulation of tactical planning, management of data and streaming video, the system also presents a service for the annotation of the interested spatial objects. Annotation deploys the web services (Alonso, Casati, Kuno, & Machiraju, 2004) exported by OpenStreetMap (OpenStreetMap) with the purpose to exploit the on-line information sources continuously updated by the social networks communities.

Two Informational Complexity Measures in Social Networks and Agent Communities

2011 ◽  
pp. 57-65
Author(s):  
António Jorge Filipe Fonseca
Keyword(s):  
Stochastic Process ◽  
Social Networks ◽  
Social Network ◽  
Structural Properties ◽  
Information Sources ◽  
Complexity Measures ◽  
Dynamic Relation ◽  
Dynamic Measures

Several informational complexity measures rely on the notion of stochastic process in order to extract hidden structural properties behind the apparent randomness of information sources. Following an equivalence approach between dynamic relation evolution within a social network and a generic stochastic process two dynamic measures of network complexity are proposed.

scholarly journals Opinion formation in time-varying social networks: The case of the naming game

2012 ◽  
Vol 86 (3) ◽  
Author(s):  
Suman Kalyan Maity ◽  
T. Venkat Manoj ◽  
Animesh Mukherjee
Keyword(s):  
Social Networks ◽  
Time Varying ◽  
Opinion Formation ◽  
Naming Game

scholarly journals Social Network Extraction Unsupervised

2021 ◽  
Vol 12 (3) ◽  
pp. 4443-4449
Author(s):  
Mahyuddin K. M. Nasution Et.al
Keyword(s):  
Artificial Intelligence ◽  
Social Networks ◽  
Information Technology ◽  
Big Data ◽  
Social Network ◽  
Data Science ◽  
Information Sources ◽  
Scientific Data

In the era of information technology, the two developing sides are data science and artificial intelligence. In terms of scientific data, one of the tasks is the extraction of social networks from information sources that have the nature of big data. Meanwhile, in terms of artificial intelligence, the presence of contradictory methods has an impact on knowledge. This article describes an unsupervised as a stream of methods for extracting social networks from information sources. There are a variety of possible approaches and strategies to superficial methods as a starting concept. Each method has its advantages, but in general, it contributes to the integration of each other, namely simplifying, enriching, and emphasizing the results.

scholarly journals Association Between Public Knowledge About COVID-19, Trust in Information Sources, and Adherence to Social Distancing: Cross-Sectional Survey (Preprint)

2020 ◽  
Author(s):  
Ilona Fridman ◽  
Nicole Lucas ◽  
Debra Henke ◽  
Christina K Zigler
Keyword(s):  
Social Networks ◽  
Information Sources ◽  
Public Knowledge ◽  
Trust In Government ◽  
Government Information ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Negatively Associated ◽  
Social Distancing ◽  
The Impact

BACKGROUND The success of behavioral interventions and policies designed to reduce the impact of the COVID-19 pandemic depends on how well individuals are informed about both the consequences of infection and the steps that should be taken to reduce the impact of the disease. OBJECTIVE The aim of this study was to investigate associations between public knowledge about COVID-19, adherence to social distancing, and public trust in government information sources (eg, the US Centers for Disease Control and Prevention), private sources (eg, FOX and CNN), and social networks (eg, Facebook and Twitter) to inform future policies related to critical information distribution. METHODS We conducted a cross-sectional survey (N=1243) between April 10 and 14, 2020. Data collection was stratified by US region and other demographics to ensure representativeness of the sample. RESULTS Government information sources were the most trusted among the public. However, we observed trends in the data that suggested variations in trust by age and gender. White and older populations generally expressed higher trust in government sources, while non-White and younger populations expressed higher trust in private sources (eg, CNN) and social networks (eg, Twitter). Trust in government sources was positively associated with accurate knowledge about COVID-19 and adherence to social distancing. However, trust in private sources (eg, FOX and CNN) was negatively associated with knowledge about COVID-19. Similarly, trust in social networks (eg, Facebook and Twitter) was negatively associated with both knowledge and adherence to social distancing. CONCLUSIONS During pandemics such as the COVID-19 outbreak, policy makers should carefully consider the quality of information disseminated through private sources and social networks. Furthermore, when disseminating urgent health information, a variety of information sources should be used to ensure that diverse populations have timely access to critical knowledge.

scholarly journals A Naming Game-Based Method for the Location of Information Source in Social Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Xue Yang ◽  
Zhiliang Zhu ◽  
Hai Yu ◽  
Yuli Zhao
Keyword(s):  
Social Networks ◽  
Information Source ◽  
Information Propagation ◽  
Propagation Models ◽  
Naming Game ◽  
Dynamic Deployment ◽  
True Source ◽  
Novel Method ◽  
Simulation Results ◽  
Source Of Information

We study herein the problem of the location of the information propagation source in social networks based on the network topology and a set of observations. We propose a concise and novel method to accurately locate the source of information using naming game theory. This study introduces the design of a dynamic deployment method that reduces considerably the number of observations and the time needed to locate the source. Moreover, it calculates the probability of each node that acts as a source based on the information provided by observations. This method can be potentially applied to various information propagation models. The simulation results reveal that the method is able to estimate the information source within a small number of hops from the true source.

scholarly journals A gentle introduction to the minimal Naming Game

2016 ◽  
Vol 30 ◽  
pp. 171-192 ◽  
Author(s):  
Andrea Baronchelli
Keyword(s):  
Social Networks ◽  
Game Model ◽  
Naming Game ◽  
Social Conventions ◽  
Global Coordination

Social conventions govern countless behaviors all of us engage in every day, from how we greet each other to the languages we speak. But how can shared conventions emerge spontaneously in the absence of a central coordinating authority? The Naming Game model shows that networks of locally interacting individuals can spontaneously self-organize to produce global coordination. Here, we provide a gentle introduction to the main features of the model, from the dynamics observed in homogeneously mixing populations to the role played by more complex social networks, and to how slight modifications of the basic interaction rules give origin to a richer phenomenology in which more conventions can co-exist indefinitely.

Two Informational Complexity Measures in Social Networks and Agent Communities

2010 ◽  
pp. 1923-1931
Author(s):  
António Jorge Filipe Fonseca
Keyword(s):  
Stochastic Process ◽  
Social Networks ◽  
Social Network ◽  
Structural Properties ◽  
Information Sources ◽  
Complexity Measures ◽  
Dynamic Relation ◽  
Dynamic Measures

Several informational complexity measures rely on the notion of stochastic process in order to extract hidden structural properties behind the apparent randomness of information sources. Following an equivalence approach between dynamic relation evolution within a social network and a generic stochastic process two dynamic measures of network complexity are proposed.

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