Using GPS Geo-tagged Social Media Data and Geodemographics to Investigate Social Differences
A Twitter Pilot Study
Bibliographic Data
| ID | 2391896 |
|---|---|
| Authors | Paul Chappell (0000-0002-3587-570X, independent scholar, corresponding author), Mike Tse (University of York), Ying Kei Tse (0000-0001-6174-0326, University of York), Minhao Zhang (0000-0002-1334-4481, University of York), Susan Moore (0000-0003-4771-2876, University of York), Susan R Moore (University of York) |
| Year | 2017 |
| Volume | 22 |
| Issue | 3 |
| Pages | 38-56 |
| Publication date | 2017-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sociological Research Online (JOURNAL) |
| Journal identifiers | ISSN: 1360-7804 • E-ISSN: 1360-7804 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/1360780417724065 |
| OpenAlex | W2755104540 |
| Language | EN |
| Citations received | 2 |
| References cited | 30 |
This article outlines a new method for investigating social position through geo-tagged Twitter data, specifically through the application of the geodemographic classification system Mosaic. The method involves the identification of a given tweeter's likely location of residence from the 'geo-tag' attached to their tweet. Using this high-resolution geographic information, each individual tweet is then attributed a geodemographic classification. This article shows that the specific application of geodemographics for discerning between different types of tweeters is problematic in some ways, but that the general process of classifying tweeters according to their position in geographical space is viable and represents a powerful new method for discerning the social position of tweeters. Further research is required in this area, as there is great potential in employing the mobile global positioning system data appended to digital by-product data to explore the intersections between geographical space and social position
Advertising · Biology · Business · Data science · Geography · Global Positioning System · Residence · Social media · Sociology · Telecommunications · World Wide Web · Computer Science · Data-Driven Disease Surveillance · Geographic Information Systems Studies · Human Mobility and Location-Based Analysis
Exploratory data analysis
Who Tweets? Deriving the Demographic Characteristics of Age, Occupation and Social Class from Twitter User Meta-Data
Where in the World Are You? Geolocation and Language Identification in Twitter
Who Tweets with Their Location? Understanding the Relationship between Demographic Characteristics and the Use of Geoservices and Geotagging on Twitter
Class Places and Place Classes Geodemographics and the Spatialization of Class
Sentient Cities Ambient intelligence and the politics of urban space
The End of the Virtual
Globalization and Belonging
The Sociology of Economic Life
Twitter power
The structure of online social networks mirrors those in the offline world
Sociology and, of and in Web 2.0
Classifying Pupils by Where They Live
Response to `The Coming Crisis of Empirical Sociology
Social media and the social sciences
After the crisis? Big Data and the methodological challenges of empirical sociology
Geodemographic Code and the Production of Space
Occupy Wall Street
SPSS as an 'Inscription Device
Welcome to 'Pikettyville'? Mapping London's alpha territories
Knowing the Tweeters
The Hidden Dimensions of the Musical Field and the Potential of the New Social Data
Some Further Reflections on the Coming Crisis of Empirical Sociology
The Coming Crisis of Empirical Sociology
Geodemographics, Software and Class
Marriage, Social Distance and the Social Space
| Unique citing works | 2 |
|---|---|
| Citations per year | 0,5 |
| Citation span | 2022 - 2025 (4) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 2 |