Happiness and the Patterns of Life: a Study of Geolocated Tweets

Overview

Journal Sci Rep

Specialty Science

Date 2013 Sep 13

PMID 24026340

Citations 29

Authors

Morgan R Frank

Lewis Mitchell

Peter Sheridan Dodds

Christopher M Danforth

Affiliations

Soon will be listed here.

Abstract

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 have 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.

Citing Articles

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Robust language-based mental health assessments in time and space through social media.

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Hsu J, Tsai R J Med Internet Res. 2022; 24(8):e38776.

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