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Inbar, Ohad; Ben-Asher, Noam; Porat, Talya; Mimran, Dudu; Shapira, Bracha; Shoval, Peretz; Meyer, Joachim; Tractinsky, Noam

doi:10.1145/1358628.1358902

Cited by 1 publication

(1 citation statement)

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“…Such personalized news has become increasingly common (Thurman & Schifferes, ), posing challenges in various domains (Shapira, Shoval, Tractinsky, & Meyer, ). Some are related to the layout of the information (e.g., Nehmadi, Meyer, Parmet, & Ben‐Asher, ) and the interface design (Inbar et al., ). However, the main challenge is the personalization process itself, from the algorithm perspective (e.g., Maidel, Shoval, Shapira, & Taieb‐Maimon, ) and from the perspective taken in our article: The user responses to personalization and user preferences.…”

Section: Introductionmentioning

confidence: 99%

Personalizing news content: An experimental study

Sela

Lavie

Inbar

et al. 2014

Asso for Info Science & Tech

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The delivery of personalized news content depends on the ability to predict user interests. We evaluated different methods for acquiring user profiles based on declared and actual interest in various news topics and items. In an experiment, 36 students rated their interest in six news topics and in specific news items and read on 6 days standard, nonpersonalized editions and personalized (basic or adaptive) news editions. We measured subjective satisfaction with the editions and expressed preferences, along with objective measures, to infer actual interest in items. Users' declared interest in news topics did not strongly predict their actual interest in specific news items. Satisfaction with all news editions was high, but participants preferred the personalized editions. User interest was weakly correlated with reading duration, article length, and reading order. Different measures predicted interest in different news topics. Explicit measures predicted interest in relatively clearly defined topics such as sports, but were less appropriate for broader topics such as science and technology. Our results indicate that explicit and implicit methods should be combined to generate user profiles. We suggest that a personalized newspaper should contain both general information and personalized items, selected based on specific combinations of measures for each of the different news topics. Based on the findings, we present a general model to decide on the personalization of news content to generate personalized editions for readers.

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