scholarly journals Inferring Urban Social Networks from Publicly Available Data

2021 ◽  
Vol 13 (5) ◽  
pp. 108
Author(s):  
Stefano Guarino  ◽  
Enrico Mastrostefano  ◽  
Massimo Bernaschi ◽  
Alessandro Celestini ◽  
Marco Cianfriglia ◽  
...  
Keyword(s):  
Social Networks ◽  
Real Data ◽  
Generative Models ◽  
Data Driven ◽  
Graph Models ◽  
Computational Epidemiology ◽  
Random Graph Models ◽  
Social Mixing ◽  
Definition Of

The definition of suitable generative models for synthetic yet realistic social networks is a widely studied problem in the literature. By not being tied to any real data, random graph models cannot capture all the subtleties of real networks and are inadequate for many practical contexts—including areas of research, such as computational epidemiology, which are recently high on the agenda. At the same time, the so-called contact networks describe interactions, rather than relationships, and are strongly dependent on the application and on the size and quality of the sample data used to infer them. To fill the gap between these two approaches, we present a data-driven model for urban social networks, implemented and released as open source software. By using just widely available aggregated demographic and social-mixing data, we are able to create, for a territory of interest, an age-stratified and geo-referenced synthetic population whose individuals are connected by “strong ties” of two types: intra-household (e.g., kinship) or friendship. While household links are entirely data-driven, we propose a parametric probabilistic model for friendship, based on the assumption that distances and age differences play a role, and that not all individuals are equally sociable. The demographic and geographic factors governing the structure of the obtained network, under different configurations, are thoroughly studied through extensive simulations focused on three Italian cities of different size.

The first flush in sewer systems

1996 ◽  
Vol 33 (9) ◽  
pp. 101-108 ◽  
Author(s):  
Agnès Saget ◽  
Ghassan Chebbo ◽  
Jean-Luc Bertrand-Krajewski
Keyword(s):  
Treatment Strategy ◽  
Real Data ◽  
First Flush ◽  
Clear Definition ◽  
Controversial Subject ◽  
Sewer Systems ◽  
Wet Weather ◽  
Definition Of ◽  
Appearance Frequency

The first flush phenomenon of urban wet weather discharges is presently a controversial subject. Scientists do not agree with its reality, nor with its influences on the size of treatment works. Those disagreements mainly result from the unclear definition of the phenomenon. The objective of this article is first to provide a simple and clear definition of the first flush and then to apply it to real data and to obtain results about its appearance frequency. The data originate from the French database based on the quality of urban wet weather discharges. We use 80 events from 7 separately sewered basins, and 117 events from 7 combined sewered basins. The main result is that the first flush phenomenon is very scarce, anyway too scarce to be used to elaborate a treatment strategy against pollution generated by urban wet weather discharges.

Networks

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Biological Networks ◽  
Generative Models ◽  
The Internet ◽  
Network Data ◽  
Computer Algorithms ◽  
Graph Models ◽  
Random Graph Models ◽  
The Social ◽  
Spectral Algorithms ◽  
Wide Availability

The study of networks, including computer networks, social networks, and biological networks, has attracted enormous interest in recent years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyse network data on an unprecendented scale, and the development of new theoretical tools has allowed us to extract knowledge from networks of many different kinds. The study of networks is broadly interdisciplinary and developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social science. This book brings together the most important breakthroughts in each of these fields and presents them in a unified fashion, highlighting the strong interconnections between work in different areas. Topics covered include the measurement of networks; methods for analysing network data, including methods developed in physics, statistics, and sociology; fundamentals of graph theory; computer algorithms, including spectral algorithms and community detection; mathematical models of networks such as random graph models and generative models; and models of processes taking place on networks.

Measurement Error and Attenuation Bias in Exponential Random Graph Models

2016 ◽  
Vol 7 (1-2) ◽  
pp. 29-54
Author(s):  
Yeaji Kim ◽  
Leonardo Antenangeli ◽  
Justin Kirkland
Keyword(s):  
Social Networks ◽  
Random Graph ◽  
Measurement Errors ◽  
Asymptotic Properties ◽  
Exponential Random Graph Models ◽  
Graph Models ◽  
Random Graph Models ◽  
Exponential Random Graph ◽  
The Face ◽  
Distributed Measurement

AbstractExponential Random Graph Models (ERGMs) are becoming increasingly popular tools for estimating the properties of social networks across the social sciences. While the asymptotic properties of ERGMs are well understood, much less is known about how ERGMs perform in the face of violations of the assumptions that drive those asymptotic properties. Given that empirical social networks rarely meet the strenuous assumptions of the ERGM perfectly, practical researchers are often in the position of knowing their coefficients are imperfect, but not knowing precisely how wrong those coefficients may be. In this research, we examine one violation of the asymptotic assumptions of ERGMs – perfectly measured social networks. Using several Monte Carlo simulations, we demonstrate that even randomly distributed measurement errors in networks under study can cause considerable attenuation in coefficients from ERGMs, and do real harm to subsequent hypothesis tests.

scholarly journals Majority Vote in Social Networks: Make Random Friends or Be Stubborn to Overpower Elites

2021 ◽  
Author(s):  
Charlotte Out ◽  
Ahad N. Zehmakan
Keyword(s):  
Social Networks ◽  
Real World ◽  
Majority Vote ◽  
Graph Models ◽  
Stabilization Time ◽  
The Real ◽  
Random Graph Models ◽  
Small Set ◽  
High Degree ◽  
Majority Model

Consider a graph G, representing a social network. Assume that initially each node is colored either black or white, which corresponds to a positive or negative opinion regarding a consumer product or a technological innovation. In the majority model, in each round all nodes simultaneously update their color to the most frequent color among their connections. Experiments on the graph data from the real world social networks (SNs) suggest that if all nodes in an extremely small set of high-degree nodes, often referred to as the elites, agree on a color, that color becomes the dominant color at the end of the process. We propose two countermeasures that can be adopted by individual nodes relatively easily and guarantee that the elites will not have this disproportionate power to engineer the dominant output color. The first countermeasure essentially requires each node to make some new connections at random while the second one demands the nodes to be more reluctant towards changing their color (opinion). We verify their effectiveness and correctness both theoretically and experimentally. We also investigate the majority model and a variant of it when the initial coloring is random on the real world SNs and several random graph models. In particular, our results on the Erdős-Rényi, and regular random graphs confirm or support several theoretical findings or conjectures by the prior work regarding the threshold behavior of the process. Finally, we provide theoretical and experimental evidence for the existence of a poly-logarithmic bound on the expected stabilization time of the majority model.

scholarly journals A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 129
Author(s):  
Xiaozhou Li ◽  
Zheying Zhang ◽  
Kostas Stefanidis
Keyword(s):  
Video Games ◽  
Video Game ◽  
Binary Classification ◽  
Game Studies ◽  
Data Driven ◽  
Software Products ◽  
Data Driven Approach ◽  
Definition Of

Playability is a key concept in game studies defining the overall quality of video games. Although its definition and frameworks are widely studied, methods to analyze and evaluate the playability of video games are still limited. Using heuristics for playability evaluation has long been the mainstream with its usefulness in detecting playability issues during game development well acknowledged. However, such a method falls short in evaluating the overall playability of video games as published software products and understanding the genuine needs of players. Thus, this paper proposes an approach to analyze the playability of video games by mining a large number of players’ opinions from their reviews. Guided by the game-as-system definition of playability, the approach is a data mining pipeline where sentiment analysis, binary classification, multi-label text classification, and topic modeling are sequentially performed. We also conducted a case study on a particular video game product with its 99,993 player reviews on the Steam platform. The results show that such a review-data-driven method can effectively evaluate the perceived quality of video games and enumerate their merits and defects in terms of playability.

scholarly journals Features of promotion services of entertainment enterprises

2020 ◽  
pp. 83-87
Author(s):  
O. V. Shpyrnya ◽  
E. A. Eremina ◽  
M. V. Koreneva
Keyword(s):  
Social Networks ◽  
Customer Service ◽  
Entertainment Industry ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality ◽  
Definition Of ◽  
High Level ◽  
The Relationship ◽  
Potential Customers

The article describes the main features of promoting the services of entertainment industry enterprises. The definition of entertainment services is given, a list of enterprises providing such services is indicated. The relationship between entertainment services and the development of the tourism and hospitality industry is revealed. Various options for promoting the services of entertainment industry enterprises are presented. Attention is paid to the importance of the process of branding the business of entertainment industry enterprises and maintaining a high level of quality of customer service. Particular attention was paid to additional elements of the marketing mix in promoting the services of entertainment industry enterprises. The basic methods of promoting services are examined, with particular emphasis on social networks VKontakte, Odnoklassniki, Instagram, Facebook. The prospects of organizing focus groups in social networks while promoting certain services in the entertainment industry are noted. It is concluded that technologies for promoting services in the entertainment industry contribute to expanding the number of potential customers, forming a group of regular customers, increasing interest from consumers, partners, and more.There is no conflict of interests.

Sign in / Sign up

Export Citation Format

Share Document