Nancy Etcoff & Hugo Liu (2017). What social media sentiment tells us about the ebb and flow of a city's moods. In A. Karandinou (Ed.): Data and Senses — Architecture, Neuroscience and the Digital Worlds, University of East London.
Etcoff, N., & Liu, H. (2017). What social media sentiment tells us about the ebb and flow of a city's moods. In A. Karandinou (Ed.), Data and Senses — Architecture, Neuroscience and the Digital Worlds. University of East London.
@incollection{etcoff2017what,
author = {Nancy Etcoff and Hugo Liu},
title = {What social media sentiment tells us about the ebb and flow of a city's moods},
booktitle = {Data and Senses — Architecture, Neuroscience and the Digital Worlds},
editor = {A. Karandinou},
publisher = {University of East London},
url = {https://starheartsong.com/papers/pdf/DataSenses2017-CityMoods.pdf},
year = {2017}
}The Positivity Pulse asks whether time-stamped, geolocated public language can complement surveys of urban mood. It collected 10,000 Santa Monica tweets and 590,000 Greater Los Angeles tweets over six days. LIWC positive and negative word counts formed a mood ratio; first-person plural and singular pronouns formed a proposed measure of social engagement. Against 1,000 tweets labeled by one judge, the classifier reported 76 percent accuracy, 91 percent precision, and 61 percent recall. The paper finds a strong relationship between its We/I and positive/negative ratios and describes different hourly patterns for residents, visitors, and Greater LA. Its boundaries are material: six days, one annotator, proxy location labels, speculative explanations for the peaks, and unresolved privacy questions.