Demography of Twitter Users in the City of London: An Exploratory Spatial Data Analysis Approach

Abstract

Geolocated tweets are not evenly spread across space, but appear in accumulations. By exploring a collection of 3 months of geolocated tweets for London, this work analyses tweet hotspots and demographic characteristics of the wards where these hotspots appear. The Twitter messages are separated into day-time and night-time tweets to support the assumption about work places and home places of Twitter users. Tweets from users with less than three posts in the investigated time period are eliminated to increase the probability of analysing locals rather than tourists. The first step in the analysis is the identification of tweet hotspots. These hotspots are wards, where increased Twitter activities are taking place, as the population figures would suggest. The subsequent step in the analysis deals with the detection of patterns in the relationship between demographic characteristics of London’s wards and the numbers of tweets. This part of the analysis employs exploratory spatial data analysis for generating hypotheses for an ordinary least squares regression analysis. The contribution of this work is the exploration of representations and analyses for investigating who Twitter users in London are.