Understanding international migration using tensor factorization

Hieu Nguyen, Kiran Garimella

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

63 Lataukset (Pure)


Understanding human migration is of great interest to demographers and social scientists. User generated digital data has made it easier to study such patterns at a global scale. Geo coded Twitter data, in particular, has been shown to be a promising source to analyse large scale human migration. But given the scale of these datasets, a lot of manual effort has to be put into processing and getting actionable insights from this data. In this paper, we explore the the feasibility of using a new tool, tensor decomposition, to understand trends in global human migration. We model human migration as a three mode tensor, consisting of (origin country, destination country, time of migration) and apply CP decomposition to get meaningful low dimensional factors. Our experiments on a large Twitter dataset spanning 5 years and over 100M tweets show that we can extract meaningful migration patterns.

Otsikko26th International World Wide Web Conference 2017, WWW 2017 Companion
ISBN (elektroninen)9781450349147
DOI - pysyväislinkit
TilaJulkaistu - 1 tammikuuta 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational World Wide Web Conference - Perth, Austraalia
Kesto: 3 huhtikuuta 20177 huhtikuuta 2017
Konferenssinumero: 26


ConferenceInternational World Wide Web Conference


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