Putting down roots: a graphical exploration of community attachment

Andee J. Kaplan () and Eric R. Hare ()
Additional contact information
Andee J. Kaplan: Iowa State University
Eric R. Hare: Iowa State University

Computational Statistics, 2019, vol. 34, issue 4, No 2, 1449-1464

Abstract: Abstract In this paper, we explore the relationships that individuals have with their communities. This work was prepared as part of the ASA Data Expo ‘13 sponsored by the Graphics Section and the Computing Section, using data provided by the Knight Foundation Soul of the Community survey. The Knight Foundation in cooperation with Gallup surveyed 43,000 people over 3 years in 26 communities across the United States with the intention of understanding the association between community attributes and the degree of attachment people feel towards their community. These include the different facets of both urban and rural communities, the impact of quality education, and the trend in the perceived economic conditions of a community over time. The goal of our work is to facilitate understanding of why people feel attachment to their communities through the use of an interactive and web-based visualization. We will explain the development and use of web-based interactive graphics, including an overview of the R package Shiny and the JavaScript library D3, focusing on the choices made in producing the visualizations and technical aspects of how they were created. Then we describe the stories about community attachment that unfolded from our analysis.

Keywords: Soul of the Community; Data Expo 2013; Interactive graphics; Shiny; D3 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s00180-018-0850-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:34:y:2019:i:4:d:10.1007_s00180-018-0850-7

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2

DOI: 10.1007/s00180-018-0850-7

Access Statistics for this article

Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik

More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().