Digital Lighthouse Platform: Understanding the Misinformation Phenomenon on WhatsApp

José Maria da Silva Monteiro Filho, Ivandro Claudino de Sá, Lucas Cabral Carneiro da Cunha, Helena Martins do Rego Barreto, Pedro Jorge Chaves Mourão
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Abstract

In the past few years, the large-scale dissemination of misinformation through social media has become a critical issue, harming the trustworthiness of legit information, social stability, democracy and public health. In many developing countries such as Brazil, India, and Mexico, one of the primary sources of misinformation is the messaging application WhatsApp. In February 2020, the Panorama Mobile Time/Opinion Box survey on mobile messaging in Brazil revealed that WhatsApp was installed on 99% of Brazilian smartphones. Among users of the application, 98% said they access it every day or almost every day. In this context, WhatsApp provides an important feature: the public groups. Many of these groups have been used to spread misinformation, especially as part of articulated political or ideological campaigns. Despite this scenario, due to WhatsApp's private messaging nature, few methods were explicitly developed to investigate the misinformation phenomenon on this platform. This tutorial provides an overview of recent developments in monitoring misinformation spreading, automatic misinformation detection, and identifying misinformation spreaders. In addition, we provide an overview of the leading open problems associated with the misinformation phenomenon and briefly examine some of the existing solutions. We hope that our tutorial can help researchers better understand Brazil's misinformation propagation and use data science methods to face this critical phenomenon.
数字灯塔平台:了解WhatsApp上的错误信息现象
在过去的几年里,通过社交媒体大规模传播虚假信息已经成为一个关键问题,损害了合法信息的可信度、社会稳定、民主和公共健康。在巴西、印度和墨西哥等许多发展中国家,错误信息的主要来源之一是即时通讯应用WhatsApp。2020年2月,Panorama Mobile Time/Opinion Box对巴西移动通讯的调查显示,99%的巴西智能手机上安装了WhatsApp。在该应用程序的用户中,98%的人表示他们每天或几乎每天都访问它。在这种情况下,WhatsApp提供了一个重要功能:公共群组。其中许多团体被用来传播错误信息,尤其是作为明确的政治或意识形态运动的一部分。尽管存在这种情况,但由于WhatsApp的私人消息性质,很少有方法被明确开发来调查该平台上的错误信息现象。本教程概述了在监视错误信息传播、自动错误信息检测和识别错误信息传播者方面的最新发展。此外,我们还概述了与错误信息现象相关的主要开放问题,并简要检查了一些现有的解决方案。我们希望我们的教程可以帮助研究人员更好地了解巴西的错误信息传播,并使用数据科学的方法来面对这一关键现象。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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