A city-wide examination of fine-grained human emotions through social media analysis.

Siriaraya, Panote; Zhang, Yihong; Kawai, Yukiko; Jeszenszky, Peter; Jatowt, Adam (2023). A city-wide examination of fine-grained human emotions through social media analysis. PLoS ONE, 18(2), e0279749. Public Library of Science 10.1371/journal.pone.0279749

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The proliferation of Social Media and Open Web data has provided researchers with a unique opportunity to better understand human behavior at different levels. In this paper, we show how data from Open Street Map and Twitter could be analyzed and used to portray detailed Human Emotions at a city wide level in two cities, San Francisco and London. Neural Network classifiers for fine-grained emotions were developed, tested and used to detect emotions from tweets in the two cites. The detected emotions were then matched to key locations extracted from Open Street Map. Through an analysis of the resulting data set, we highlight the effect different days, locations and POI neighborhoods have on the expression of human emotions in the cities.

Item Type:

Journal Article (Original Article)

Division/Institute:

06 Faculty of Humanities > Department of Linguistics and Literary Studies > Institute of Germanic Languages > Applied Linguistics and Communication Science
06 Faculty of Humanities > Other Institutions > Walter Benjamin Kolleg (WBKolleg) > Center for the Study of Language and Society (CSLS)

UniBE Contributor:

Jeszenszky, Péter

Subjects:

100 Philosophy
800 Literature, rhetoric & criticism
400 Language
400 Language > 430 German & related languages
900 History
300 Social sciences, sociology & anthropology

ISSN:

1932-6203

Publisher:

Public Library of Science

Language:

English

Submitter:

Pubmed Import

Date Deposited:

06 Feb 2023 11:25

Last Modified:

12 Jan 2024 10:29

Publisher DOI:

10.1371/journal.pone.0279749

PubMed ID:

36724143

BORIS DOI:

10.48350/178286

URI:

https://boris.unibe.ch/id/eprint/178286

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