Entendre, a Social Bot Detection Tool for Niche, Fringe, and Extreme Social Media

Fuente: arXiv
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Hauptverfasser: Venkatesh, Pranav, Vinton, Kami, Murthy, Dhiraj, Sharp, Kellen, Kolluri, Akaash
Format: Preprint
Veröffentlicht: 2024
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author Venkatesh, Pranav
Vinton, Kami
Murthy, Dhiraj
Sharp, Kellen
Kolluri, Akaash
author_facet Venkatesh, Pranav
Vinton, Kami
Murthy, Dhiraj
Sharp, Kellen
Kolluri, Akaash
contents Social bots-automated accounts that generate and spread content on social media-are exploiting vulnerabilities in these platforms to manipulate public perception and disseminate disinformation. This has prompted the development of public bot detection services; however, most of these services focus primarily on Twitter, leaving niche platforms vulnerable. Fringe social media platforms such as Parler, Gab, and Gettr often have minimal moderation, which facilitates the spread of hate speech and misinformation. To address this gap, we introduce Entendre, an open-access, scalable, and platform-agnostic bot detection framework. Entendre can process a labeled dataset from any social platform to produce a tailored bot detection model using a random forest classification approach, ensuring robust social bot detection. We exploit the idea that most social platforms share a generic template, where users can post content, approve content, and provide a bio (common data features). By emphasizing general data features over platform-specific ones, Entendre offers rapid extensibility at the expense of some accuracy. To demonstrate Entendre's effectiveness, we used it to explore the presence of bots among accounts posting racist content on the now-defunct right-wing platform Parler. We examined 233,000 posts from 38,379 unique users and found that 1,916 unique users (4.99%) exhibited bot-like behavior. Visualization techniques further revealed that these bots significantly impacted the network, amplifying influential rhetoric and hashtags (e.g., #qanon, #trump, #antilgbt). These preliminary findings underscore the need for tools like Entendre to monitor and assess bot activity across diverse platforms.
format Preprint
id arxiv_https___arxiv_org_abs_2408_06900
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Entendre, a Social Bot Detection Tool for Niche, Fringe, and Extreme Social Media
Venkatesh, Pranav
Vinton, Kami
Murthy, Dhiraj
Sharp, Kellen
Kolluri, Akaash
Computers and Society
Artificial Intelligence
Human-Computer Interaction
Social and Information Networks
J.4; I.2; I.7; K.4
Social bots-automated accounts that generate and spread content on social media-are exploiting vulnerabilities in these platforms to manipulate public perception and disseminate disinformation. This has prompted the development of public bot detection services; however, most of these services focus primarily on Twitter, leaving niche platforms vulnerable. Fringe social media platforms such as Parler, Gab, and Gettr often have minimal moderation, which facilitates the spread of hate speech and misinformation. To address this gap, we introduce Entendre, an open-access, scalable, and platform-agnostic bot detection framework. Entendre can process a labeled dataset from any social platform to produce a tailored bot detection model using a random forest classification approach, ensuring robust social bot detection. We exploit the idea that most social platforms share a generic template, where users can post content, approve content, and provide a bio (common data features). By emphasizing general data features over platform-specific ones, Entendre offers rapid extensibility at the expense of some accuracy. To demonstrate Entendre's effectiveness, we used it to explore the presence of bots among accounts posting racist content on the now-defunct right-wing platform Parler. We examined 233,000 posts from 38,379 unique users and found that 1,916 unique users (4.99%) exhibited bot-like behavior. Visualization techniques further revealed that these bots significantly impacted the network, amplifying influential rhetoric and hashtags (e.g., #qanon, #trump, #antilgbt). These preliminary findings underscore the need for tools like Entendre to monitor and assess bot activity across diverse platforms.
title Entendre, a Social Bot Detection Tool for Niche, Fringe, and Extreme Social Media
topic Computers and Society
Artificial Intelligence
Human-Computer Interaction
Social and Information Networks
J.4; I.2; I.7; K.4
url https://arxiv.org/abs/2408.06900