Source-linked AI summary
Happiness and the Patterns of Life: A Study of Geolocated Tweets
Morgan R. Frank, Lewis Mitchell, Peter S. Dodds, Christopher M. Danforth
TL;DR
The paper characterizes mobility using geolocated Twitter trajectories and examines how word usage varies with distance from individuals’ expected locations. It reports movement-shape regularities, city-level gyradius patterns, and a small happiness-related signal in word usage.
Problem
Twitter-based mobility analysis is constrained by uncertainty about the demographic composition of users who regularly geolocate their messages.
Method
The study normalizes individual trajectories using gyradius and principal-axis direction, then analyzes normalized locations and associated word usage.
Results
Individuals’ movement is concentrated along a principal axis, while word shifts indicate that tweets farther from expected locations contain fewer negative words and lower happiness relative to tweets near home.
Takeaways & Limitations
Geolocated Twitter data can jointly reveal large-scale mobility structure and small changes in expressed happiness associated with movement.
Takeaways & Limitations
The study cannot quantify the demographic composition of users who geolocate a large share of their messages.
Abstract
from arXiv · showhide
The patterns of life exhibited by large populations have been described and modeled both as a basic science exercise and for a range of applied goals such as reducing automotive congestion, improving disaster response, and even predicting the location of individuals. However, these studies previously had limited access to conversation content, rendering changes in expression as a function of movement invisible. In addition, they typically use the communication between a mobile phone and its nearest antenna tower to infer position, limiting the spatial resolution of the data to the geographical region serviced by each cellphone tower. We use a collection of 37 million geolocated tweets to characterize the movement patterns of 180,000 individuals, taking advantage of several orders of magnitude of increased spatial accuracy relative to previous work. Employing the recently developed sentiment analysis instrument known as the 'hedonometer', we characterize changes in word usage as a function of movement, and find that expressed happiness increases logarithmically with distance from an individual's average location.