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Those were the days: learning to rank social media posts for reminiscence

  • Kaweh Djafari Naini
  • Ricardo Kawase
  • Nattiya Kanhabua
  • Claudia Niederée
  • Ismail Sengor Altingovde
Social Media for Personalization and Search
  • 37 Downloads

Abstract

Social media posts are a great source for life summaries aggregating activities, events, interactions and thoughts of the last months or years. They can be used for personal reminiscence as well as for keeping track with developments in the lives of not-so-close friends. One of the core challenges of automatically creating such summaries is to decide which posts are memorable, i.e., should be considered for retention and which ones to forget. To address this challenge, we design and conduct user evaluation studies and construct a corpus that captures human expectations towards content retention. We analyze this corpus to identify a small set of seed features that are most likely to characterize memorable posts. Next, we compile a broader set of features that are leveraged to build general and personalized machine-learning models to rank posts for retention. By applying feature selection, we identify a compact yet effective subset of these features. The models trained with the presented feature sets outperform the baseline models exploiting an intuitive set of temporal and social features.

Keywords

Learning to rank Letor Social media Personalization Personalized ranking Content retention Social features Feature selection Facebook 

Notes

Funding

I.S. Altingovde is supported by Turkish Academy of Sciences Distinguished Young Scientist Award (TUBA-GEBIP 2016). This work was partially funded by the DFG Project “Managed Forgetting” (Contract Number NI-1760/1-1).

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Kaweh Djafari Naini
    • 1
  • Ricardo Kawase
    • 1
  • Nattiya Kanhabua
    • 2
  • Claudia Niederée
    • 1
  • Ismail Sengor Altingovde
    • 3
  1. 1.L3S Research CenterHannoverGermany
  2. 2.NTENT Inc.BarcelonaSpain
  3. 3.Computer Engineering DepartmentMiddle East Technical UniversityAnkaraTurkey

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