What Users Prefer and Why: A User Study on Effective Presentation Styles of Opinion Summarization - Human-Computer Interaction – INTERACT 2015
Conference Papers Year : 2015

What Users Prefer and Why: A User Study on Effective Presentation Styles of Opinion Summarization

Xiaojun Yuan
  • Function : Author
  • PersonId : 1018513
Ning Sa
  • Function : Author
  • PersonId : 1018514
Grace Begany
  • Function : Author
  • PersonId : 1018515
Huahai Yang
  • Function : Author
  • PersonId : 1018516

Abstract

Opinion Summarization research addresses how to help people in making appropriate decisions in an effective way. This paper aims to help users in their decision-making by providing them effective opinion presentation styles. We carried out two phases of experiments to systematically compare usefulness of different types of opinion summarization techniques. In the first crowd-sourced study, we recruited 46 turkers to generate high quality summary information. This first phase generated four styles of summaries: Tag Clouds, Aspect Oriented Sentiments, Paragraph Summary and Group Sample. In the follow-up second phase, 34 participants tested the four styles in a card sorting experiment. Each participant was given 32 cards with 8 per presentation styles and completed the task of grouping the cards into five categories in terms of the usefulness of the cards. Results indicated that participants preferred Aspect Oriented Sentiments the most and Tag cloud the least. Implications and hypotheses are discussed.
Fichier principal
Vignette du fichier
346942_1_En_20_Chapter.pdf (669.11 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01599891 , version 1 (02-10-2017)

Licence

Identifiers

Cite

Xiaojun Yuan, Ning Sa, Grace Begany, Huahai Yang. What Users Prefer and Why: A User Study on Effective Presentation Styles of Opinion Summarization. 15th Human-Computer Interaction (INTERACT), Sep 2015, Bamberg, Germany. pp.249-264, ⟨10.1007/978-3-319-22668-2_20⟩. ⟨hal-01599891⟩
110 View
197 Download

Altmetric

Share

More