Journal article
The Pod People: Understanding Manipulation of Social Media Popularity via Reciprocity Abuse
WEB CONFERENCE 2020: Proceedings of The World Wide Web Conference (WWW 2020), pp 1874-1884
01 Jan 2020
Abstract
Online Social Network (OSN) Users' demand to increase their account popularity has driven the creation of an underground ecosystem that provides services or techniques to help users manipulate content curation algorithms. One method of subversion that has recently emerged occurs when users form groups, called pods, to facilitate reciprocity abuse, where each member reciprocally interacts with content posted by other members of the group. We collect 1.8 million Instagram posts that were posted in pods hosted on Telegram. We first summarize the properties of these pods and how they are used, uncovering that they are easily discoverable by Google search and have a low barrier to entry. We then create two machine learning models for detecting Instagram posts that have gained interaction through two different kinds of pods, achieving 0.91 and 0.94 AUC, respectively. Finally, we find that pods are effective tools for increasing users' Instagram popularity, we estimate that pod utilization leads to a significantly increased level of likely organic comment interaction on users' subsequent posts.
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Details
- Title
- The Pod People: Understanding Manipulation of Social Media Popularity via Reciprocity Abuse
- Creators
- Janith Weerasinghe - New York UniversityBailey Flanigan - Drexel UniversityAviel Stein - Drexel UniversityDamon McCoy - New York UniversityRachel Greenstadt - New York University
- Publication Details
- WEB CONFERENCE 2020: Proceedings of The World Wide Web Conference (WWW 2020), pp 1874-1884
- Conference
- The World Wide Web Conference (WWW 2020) (Taipei, Taiwan, 20 Apr 2020–24 Apr 2020)
- Publisher
- Assoc Computing Machinery
- Number of pages
- 11
- Grant note
- 1931005; 1814816 / National Science Foundation; National Science Foundation (NSF)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- College of Computing and Informatics
- Web of Science ID
- WOS:000626273301084
- Scopus ID
- 2-s2.0-85086587585
- Other Identifier
- 1450370233; 9781450370233; 991021876911704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Telecommunications