Title: Controlling astroturfing on the internet: a survey on detection techniques and research challenges

Authors: Syed Mahbub; Eric Pardede; A.S.M. Kayes; Wenny Rahayu

Addresses: Department of Computer Science and Information Technology, La Trobe University, Melbourne, Australia ' Department of Computer Science and Information Technology, La Trobe University, Melbourne, Australia ' Department of Computer Science and Information Technology, La Trobe University, Melbourne, Australia ' Department of Computer Science and Information Technology, La Trobe University, Melbourne, Australia

Abstract: Astroturfing is one of the most impactful threats on today's internet. It is the process of masking and portraying a doctored message to the general population in a way as though it originated from the grass-root level. The concept of astroturfing detection is started to gain popularity among researchers in social media, e-commerce and politics. With the recent growth of crowdsourcing systems, astroturfing is also creating a profound impact on people's opinions. Political blogs, news portals and review websites are being flooded with astroturfs. Some groups are using astroturfing to promote their interest and some are using it to demote the interest of competitors. Researchers have adopted many approaches to detect astroturfing on the web. These approaches include content analysis techniques, individual and group identification techniques, analysing linguistic features, authorship attribution techniques, machine learning and so on. We present a taxonomy of these approaches based on the key issues in online astroturfing detection techniques and discuss the relevant approaches in each category. The paper also summarises the discussed literature and highlights research challenges and directions for future work that have not aligned with the currently available research.

Keywords: astroturfing detection; astroturf; social media astroturfing; crowdturfing; collusive spamming.

DOI: 10.1504/IJWGS.2019.099561

International Journal of Web and Grid Services, 2019 Vol.15 No.2, pp.139 - 158

Received: 04 May 2018
Accepted: 12 Dec 2018
Published online: 09 May 2019 *

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