A Methodological Template to Construct Ground Truth of Authentic and Fake Online Reviews

Research output: Chapter in Book/Report/Conference proceedingConference contribution


With the emergence of opinion spam, scholars in recent years have been investigating how to distinguish between authentic and fake online reviews. In this research area however, constructing ground truth has been a tricky problem. When labeled datasets of authentic and fake reviews are unavailable, it becomes impossible to systematically investigate differences between the two. In light of this problem, the goal of this paper is three-fold: (1) To review existing approaches of developing ground truth, (2) To present an improved methodological template to construct ground truth, and (3) To conduct a quality-check of the newly constructed ground truth. The existing approaches are dissected to identify several peculiarities. The new approach invests in mitigating pitfalls in the current approaches. In the newly constructed ground truth, authentic reviews were found to be not easily distinguishable from fake reviews. Finally, new research directions are identified with the hope that scholars would be able to stay ahead in their relentless race against spammers.
Original languageEnglish
Title of host publication2018 IEEE International Conference on Data Science and Advanced Analytics
Number of pages8
Publication statusPublished - 2018
EventIEEE International Conference on Data Science and Advanced Analytics - Turin, Turin, Italy
Duration: 1 Oct 20184 Oct 2018


ConferenceIEEE International Conference on Data Science and Advanced Analytics
Abbreviated titleDSAA
Internet address

Bibliographical note

© IEEE, 2018. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details


  • fake review
  • ground truth
  • online review
  • opinion spam
  • spam 2.0

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