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dc.contributor.author
Lerman, Kristina
dc.contributor.author
Arora, Megha
dc.contributor.author
Gallegos, Luciano
dc.contributor.author
Kumaraguru, Ponnurangam
dc.contributor.author
Garcia, David
dc.date.accessioned
2017-06-11T23:25:07Z
dc.date.available
2017-06-11T23:25:07Z
dc.date.issued
2015
dc.identifier.uri
http://hdl.handle.net/20.500.11850/111050
dc.description.abstract
The social connections, or ties, individuals create affect their life outcomes, for example, by providing novel information that leads to new jobs or career opportunities. A host of socioeconomic and cognitive factors are believed to affect social interactions, but few of these factors have been empirically validated. In this research work, we extracted a large corpus of data from a popular social media platform that consists of geo-referenced messages, or tweets, posted from a major US metropolitan area. We linked these tweets to US Census data through their locations. This allowed us to measure emotions expressed in tweets posted from a specific area, and also use that area's socioeconomic and demographic characteristics in the analysis. We extracted the structure of social interactions from the people mentioned in tweets from that area. We find that at an aggregate level, areas where social media users engage in stronger, less diverse online social interactions are those where they express more negative emotions, like sadness and anger. With respect to demographics, these areas have larger numbers of Hispanic residents, lower mean household income, and lower education levels. Conversely, areas with weaker, more diverse online interactions are associated with happier, more positive feelings and also have better educated, younger and higher-earning residents. Our work highlights the value of linking social media data to traditional data sources, such as US Census, to drive novel analysis of online behavior.
dc.language.iso
en
dc.publisher
Cornell University
dc.title
Emotions, Demographics and Sociability in Twitter Interactions
dc.type
Working Paper
ethz.journal.title
arXiv
ethz.pages.start
arXiv:1510.07090
ethz.size
10 p.
ethz.notes
See also: http://e-citations.ethbib.ethz.ch/view/pub:180914.
ethz.publication.place
Ithaca, NY
ethz.publication.status
published
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03682 - Schweitzer, Frank / Schweitzer, Frank
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03682 - Schweitzer, Frank / Schweitzer, Frank
ethz.identifier.url
http://arxiv.org/abs/1510.07090v2
ethz.date.deposited
2017-06-11T23:25:21Z
ethz.source
ECIT
ethz.identifier.importid
imp593653ff149fb75739
ethz.ecitpid
pub:172385
ethz.eth
yes
ethz.availability
Metadata only
ethz.rosetta.installDate
2017-07-12T13:41:58Z
ethz.rosetta.lastUpdated
2018-11-02T21:45:56Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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