What Is So “Hot” in Heatmap? Qualitative Code Cluster Analysis with Foursquare Venue
Bibliographic Data
| ID | 14701784 |
|---|---|
| Authors | Ilyoung Hong (0000-0002-9617-9978, Namseoul University, corresponding author), Jin‐kyu Jung (0000-0001-7222-2532, University of Washington Bothell), Jin-Kyu Jung (0000-0003-4971-4146, University of Washington Bothell) |
| Year | 2017 |
| Volume | 52 |
| Issue | 4 |
| Pages | 332-348 |
| Publication date | 2017-12-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Cartographica The International Journal for Geographic Information and Geovisualization (JOURNAL) |
| Journal identifiers | ISSN: 0317-7173 • E-ISSN: 1911-9925 |
| Publisher | University of Toronto Press Inc. (UTPress) (PUBLISHER) |
| DOI | 10.3138/cart.52.4.2016-0005 |
| OpenAlex | W2780647572 |
| Language | EN |
| Citations received | 1 |
| References cited | 34 |
Foursquare is a popular Web service and a representative location-based social network (LBSN) service using position data. Heatmap is a widely used means of geovisualization for analyzing social data with locational values. Until now, heatmap analysis of LBSN has focused on identifying quantitative distribution and patterns, with little consideration of the qualitative analysis of data content. Based on a case study of Foursquare venues and user-created content in Seattle, WA, this study conducts analyses assessing both the quantitative spatial distribution and the qualitative characteristics of coffee shops in the Seattle metropolitan area. It specifically proposes a new analytical method referred to as “code cluster,” which is designed to employ quantitative and qualitative approaches simultaneously. The significance of this method is its capacity to explain geographical differences in terms of qualitative traits in cluster regions, in addition to analyzing their spatial characteristics and distributions. In introducing this new hybrid approach, our aims are to reflect the original intent and essence of the data throughout the research process and to make further efforts to analyze and interpret the contextualized meanings. This will be possible through integration of advanced spatial analysis, geovisualization, and qualitative research that build on current geographic and geovisual research with big data
Cluster (spacecraft · Data mining · Data science · Geography · Geovisualization · Information retrieval · Information visualization · Machine learning · Metropolitan area · Qualitative property · Qualitative research · Service (business · Social science · Sociology · Visualization · Computer Science · Data-Driven Disease Surveillance · Geographic Information Systems Studies · Human Mobility and Location-Based Analysis
Grounded theory in practice
Social Media Mining
Grounded Theory for Qualitative Research
Qualitative Media Analysis
The Geography of Happiness
The Interpretation of Cultures
Geographic Information Science
Grounded Theory in Practice
Towards Qualitative Geovisual Analytics
Still Deconstructing the Map
Deconstructing the Map after 25 Years
Another Politics Is Possible
A New Qualitative GIS Method for Investigating Neighbourhood Characteristics Using a Tablet
Geography and the future of big data, big data and the future of geography
Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr
What are we ‘tweeting’ about obesity? Mapping tweets with topic modeling and Geographic Information System
Harvesting ambient geospatial information from social media feeds
The emergent urban imaginaries of geosocial media
Crossing the qualitative-quantitative chasm I
Rethinking maps
Code clouds
Prospects for Geography as an Interdisciplinary Discipline
Content clouds as exploratory qualitative data analysis
Crossing the qualitative- quantitative divide II
The matter of ‘virtual’ geographies
Geo-Narrative
Training the eye
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,2 |
| Citation span | 2021 - 2021 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |