A survey on assessment and ranking methodologies for user-generated content on the web

Elaheh Momeni, Claire Cardie, Nicholas Diakopoulos

Research output: Contribution to journalReview articlepeer-review

16 Scopus citations

Abstract

User-generated content (UGC) on theWeb, especially on social media platforms, facilitates the association of additional information with digital resources; thus, it can provide valuable supplementary content. However, UGC varies in quality and, consequently, raises the challenge of how to maximize its utility for a variety of end-users. This study aims to provide researchers andWeb data curators with comprehensive answers to the following questions: What are the existing approaches and methods for assessing and ranking UGC? What features and metrics have been used successfully to assess and predict UGC value across a range of application domains? What methods can be effectively employed to maximize that value? This survey is composed of a systematic review of approaches for assessing and ranking UGC: results are obtained by identifying and comparing methodologies within the context of short text-based UGC on the Web. Existing assessment and ranking approaches adopt one of four framework types: the community-based framework takes into consideration the value assigned to content by a crowd of humans, the end-user-based framework adapts and personalizes the assessment and ranking process with respect to a single end-user, the designer-based framework encodes the software designer's values in the assessment and ranking method, and the hybrid framework employs methods from more than one of these types. This survey suggests a need for further experimentation and encourages the development of new approaches for the assessment and ranking of UGC.

Original languageEnglish (US)
Article number2811282
JournalACM Computing Surveys
Volume48
Issue number3
DOIs
StatePublished - Dec 1 2015

Keywords

  • Adaptive
  • Assessment
  • Human centered
  • Interactive
  • Machine centered
  • Ranking
  • Social media
  • User-generated content

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'A survey on assessment and ranking methodologies for user-generated content on the web'. Together they form a unique fingerprint.

Cite this