Applied Network Science

Abstract We present an urban science framework to characterize phone users’ exposure to different street context types based on network science, geographical information systems (GIS), daily individual trajectories, and street imagery. We consider street context as the inferred usage of the street, based on its buildings and construction, categorized in nine possible labels. The labels define whether the street is residential, commercial or downtown, throughway or not, and other special categories. We apply the analysis to the City of Boston, considering daily trajectories synthetically generated with a model based on call detail records (CDR) and images from Google Street View. Images are categorized both manually and using artificial intelligence (AI). We focus on the city’s four main racial/ethnic demographic groups (White, Black, Hispanic and Asian), aiming to characterize the differences in what these groups of people see during their daily activities. Based on daily trajectories, we reconstruct most common paths over the street network. We use street demand (number of times a street is included in a trajectory) to detect each group’s most relevant streets and regions. Based on their street demand, we measure the street context distribution for each group. The inclusion of images allows us to quantitatively measure the prevalence of each context and points to qualitative differences on where that context takes place. Other AI methodologies can further exploit these differences. This approach presents the building blocks to further studies that relate mobile devices’ dynamic records with the differences in urban exposure by demographic groups. The addition of AI-based image analysis to street demand can power up the capabilities of urban planning methodologies, compare multiple cities under a unified framework, and reduce the crudeness of GIS-only mobility analysis. Shortening the gap between big data-driven analysis and traditional human classification analysis can help build smarter and more equal cities while reducing the efforts necessary to study a city’s characteristics.

Ariel Salgado

Weixin Li

Fahad Alhasoun

Inés Caridi

Marta Gonzalez

Street context of various demographic groups in their daily mobility

不同人口群体日常流动的街道环境

This paper presents a comprehensive survey of network analysis research on the film industry, aiming to evaluate its emergence as a field of study and identify potential areas for further research. Many foundational network studies made use of the abundant data from the Internet Movie Database (IMDb) to test network methodologies. This survey focuses more specifically on examining research that employs network analysis to evaluate the film industry itself, revealing the social and business relationships involved in film production, distribution, and consumption. The paper adopts a classification approach based on node type and summarizes the key contributions in relation to each. The review provides insights into the structure and interconnectedness of the field, highlighting clusters of debates and shedding light on the areas in need of further theoretical and methodological development. In addition, this survey contributes to understanding film industry network analysis and informs researchers interested in network methods within the film industry and related cultural sectors.

Aresh Dadlani

Vi Vo

Ayushi Khemka

Sophie Talalay Harvey

Aigul Kantoro Kyzy

Pete Jones

Deb Verhoeven

Leading by the nodes: a survey of film industry network analysis and datasets

节点引领：电影产业网络分析与数据集综述

The friendship paradox states that, on average, people have fewer friends than their friends do. This can lead to social perception biases, such as the belief that one's friends are more socially engaged than oneself. In a recent paper, we investigated the consequences of this type of social comparison for content sharing behavior in online social networks (Medhat and Iyer, The Friendship paradox and social network participation, international workshop on complex networks and their applications, pp 301–315, 2023). We simulated a scenario where people compare the feedback that their own content receives to the feedback that their friends' content receives and adjust their sharing based on the comparison. If sharing and feedback rates are initially uniform over individuals, then feedback disparities initially depend solely upon the local structural friending paradox. These structurally induced disparities may then induce sharing disparities that further amplify (or potentially, reduce) feedback disparities, triggering cycles of updates of sharing rates and feedback disparities. In our previous work, we observed that monotonic responses to social comparisons, where larger disparities result in greater behavioral changes, led to an asymptotic decline in overall network sharing. In this paper, we extend our earlier work by studying fundamental properties of our friendship-paradox-induced sharing trajectories (FIT) method. We analyze how sharing rates trend when it is dictated by both observed feedback disparities and activity thresholds for collective behavior. We also evaluate the iterative impact of FIT on network nodes, as a measure of node centrality in a network, finding it to have the ability to identify central nodes at a community level and to do so at a lower computational complexity than community detection, a property not matched by commonly used node centrality methods such as betweeness, closeness and degree centrality.

Ahmed Medhat

Shankar Iyer

Exploring systemic effects of the friendship paradox on social network participation

探索友谊悖论对社交网络参与的系统性影响

Otilija Jurakovaite

Asta Gaigaliene

Regionalization and continuing globalization scenarios as a result of re-globalization: a matter of ally-familiarity proximity in multiplex financial network

再全球化背景下的区域化与持续全球化情景：多重金融网络中的盟友-熟悉度邻近性

We report on a field experiment that has been designed to provide evidence of causal effects underlying the micro-foundations of public policy diffusion across the U.S. states. The aim of our study is to test how and if cross-state legislator level connections serve as a vector through which support for policies diffuses. We measure a novel cross-state legislative network dataset in which two legislators are connected through co-signing environmental policy statements organized by the National Caucus of Environmental Legislators. We survey legislators' support for policies proposed in other states, and randomize the degree of information included in the policy description regarding support by other legislators in the network. We contribute to our understanding of state legislative politics, policy networks, and interest group politics. We focus on environmental policy due to the inherently nationalized consequences of state and local policy innovations.

Ishita Gopal

Bruce Desmarais

Legislative support for environmental policy innovation: an experimental test for diffusion through a cross-state policy network

立法支持环境政策创新：跨州政策网络扩散的实验检验

Abstract Multilayer networks (MLNs) have become a popular choice to model complex systems. However, current MLN engineering solutions, that is, systems and methods to store, manipulate, and support the analysis of MLNs, are challenged by the size and complexity of contemporary sources of network data. We assess the maturity level of the MLN engineering ecosystem through an analysis of software libraries for MLNs, focusing on supported functionality, operators and their scalability. Based on this analysis, we provide an overview of the current status of the MLN engineering landscape, compile a list of current limitations to be addressed and propose future developments for more effective and broadly applicable MLN engineering solutions.

Abbreviation	Appl. Netw. Sci.
Journal Impact	1.20
Quartiles(Global)	MULTIDISCIPLINARY SCIENCES(Q2)

ISSN	2364-8228
h-index	27

Publication Information	Publisher: Springer Nature，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2016，Proportion of original research papers: 96.47%，Self Citation Rate:7.70%， Gold OA Rate: 100.00%
Journal Fees	$1490Details
Average review cycle	网友分享经验：5 Weeks

Applied Network Science

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Street context of various demographic groups in their daily mobility

Leading by the nodes: a survey of film industry network analysis and datasets

Exploring systemic effects of the friendship paradox on social network participation

Regionalization and continuing globalization scenarios as a result of re-globalization: a matter of ally-familiarity proximity in multiplex financial network

Legislative support for environmental policy innovation: an experimental test for diffusion through a cross-state policy network

Legislative support for environmental policy innovation: an experimental test for diffusion through a cross-state policy network

Regionalization and continuing globalization scenarios as a result of re-globalization: a matter of ally-familiarity proximity in multiplex financial network

Leading by the nodes: a survey of film industry network analysis and datasets

Exploring systemic effects of the friendship paradox on social network participation

Current challenges in multilayer network engineering