Crowdsourced App Review Manipulation Conference Paper uri icon

abstract

  • 2017 ACM. With the rapid adoption of smartphones worldwide and the reliance on app marketplaces to discover new apps, these marketplaces are critical for connecting users with apps. And yet, the user reviews and ratings on these marketplaces may be strategically targeted by app developers. We investigate the use of crowdsourcing platforms to manipulate app reviews. We find that (i) apps targeted by crowdsourcing platforms are rated significantly higher on average than other apps; (ii) the reviews themselves arrive in bursts; (iii) app reviewers tend to repeat themselves by relying on some standard repeated text; and (iv) apps by the same developer tend to share a more similar language model: if one app has been targeted, it is likely that many of the other apps from the same developer have also been targeted.

name of conference

  • Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

published proceedings

  • SIGIR'17: PROCEEDINGS OF THE 40TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL

author list (cited authors)

  • Li, S., Caverlee, J., Niu, W., & Kaghazgaran, P.

citation count

  • 7

complete list of authors

  • Li, Shanshan||Caverlee, James||Niu, Wei||Kaghazgaran, Parisa

editor list (cited editors)

  • Kando, N., Sakai, T., Joho, H., Li, H., Vries, A., & White, R. W.

publication date

  • August 2017