Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Relationship Formation

Relationship Formation

What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...

Factorial Design

Factorial Design

Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...

Levels of Use of a GIS

Levels of Use of a GIS

Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...

Manipulation and Analysis

Manipulation and Analysis

GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...

Network Covalent Solids

Network Covalent Solids

Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...

Selected Data About Geographic Locations

Selected Data About Geographic Locations

Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Nitrogen-driven ferromagnetism and perpendicular magnetic anisotropy in two-dimensional transition-metal nitrides.

The Journal of chemical physics·2026

Same author

Remote spin-state engineering of Fe<sub>2</sub>Ni clusters <i>via</i> a graphdiyne-MXene heterointerface for boosted N<sub>2</sub> reduction.

Chemical communications (Cambridge, England)·2026

Same author

Distinct Defence Mechanisms of Allelopathic Rice Against Quinclorac-Susceptible and -Resistant Barnyardgrass: Involvement of Specific Metabolites and Rhizosheath Microbiota.

Plant biotechnology journal·2026

Same author

Field-Deployable Cross-Priming Amplification Coupled with Molecular Beacon Fluorometry for On-Site Detection of Citrus Huanglongbing Pathogen.

Journal of agricultural and food chemistry·2026

Same author

miR-126-3p Inhibits the Apoptosis of Ovarian Granulosa Cells in Polycystic Ovary Syndrome by Targeting SLC7A5.

The Tohoku journal of experimental medicine·2025

Same author

Lacritin cleavage-potentiated targeting of iron - respiratory reciprocity promotes bacterial death.

The Journal of biological chemistry·2025

Search research articles

Related Experiment Video

Updated: Aug 1, 2025

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Spatial social network research: a bibliometric analysis.

Ling Wu¹, Qiong Peng², Michael Lemke³

¹Texas Research Data Center, Texas A&M University, College Station, USA.

Computational Urban Science

|April 25, 2023

Summary

Spatial social network studies are rapidly growing, driven by big data and human mobility research. Key trends include social media analysis and geographic information systems (GIS) for understanding urban dynamics.

Keywords:

Geography Social media Social network

More Related Videos

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Related Experiment Videos

Last Updated: Aug 1, 2025

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Area of Science:

Spatial Social Network Studies
Human Dynamics
Urban Geography

Background:

The field of spatial social network studies is experiencing dynamic growth.
Increased attention is focused on fine-scale human dynamics in urban and mobile environments.
Growth is evidenced by scientific output, domain categories, leading journals, countries, institutions, and keywords.

Purpose of the Study:

To analyze the growth and trends in spatial social network studies over the past 20 years.
To identify key journals, countries, institutions, and keywords driving research in this field.
To highlight emerging research trends and future directions in spatial social network analysis.

Main Methods:

Bibliometric analysis of scientific outputs in spatial social network studies.
Identification of frequently used keywords and their evolution over time.
Analysis of publication trends across journals, countries, and institutions.

Main Results:

Top journals include Journal of Economic Geography, Annals of the Association of American Geographers, and Urban Studies.
Leading countries are the United States, United Kingdom, and China, with significant international collaboration.
Prominent institutions include Wuhan University, University of Oxford, and Harvard University.
Key historical keywords: Twitter, big data, networks, spatial analysis, social capital.
Emerging keywords: social media, human mobility, machine learning, GIS, location-based social networks, data mining, location-based services.

Conclusions:

Spatial social network studies are a rapidly evolving field with increasing international collaboration.
The rise of big data, social media, and GIS is shaping future research directions.
Continued focus on human mobility and advanced analytical techniques like machine learning is expected.