Predicting User Views in Online News

Daniel Hardt, Owen Rambow

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

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Abstrakt

We analyze user viewing behavior on anonline news site. We collect data from64,000 news articles, and use text featuresto predict frequency of user views.We compare predictiveness of the headlineand “teaser” (viewed before clicking) andthe body (viewed after clicking). Both arepredictive of clicking behavior, with thefull article text being most predictive.
OriginalsprogEngelsk
TitelProceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism
RedaktørerOctavian Popescu, Carlo Strapparava
UdgivelsesstedStroudsburg, PA
ForlagAssociation for Computational Linguistics
Publikationsdato2017
Sider7-12
ISBN (Elektronisk)9781945626883
StatusUdgivet - 2017
BegivenhedNatural Language Processing Meets Journalism: EMNLP 2017 Workshop - København, Danmark
Varighed: 7 sep. 20177 sep. 2017

Workshop

WorkshopNatural Language Processing Meets Journalism
LandDanmark
ByKøbenhavn
Periode07/09/201707/09/2017

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