Disinformation的研究进展、利益分析及应对——基于CiteSpace和5W2H分析法

以Web of Science数据库核心合集收录的1993篇文献为研究对象,采用CiteSpace可视化软件梳理Disinformation的研究动态和演进过程,使用5W2H分析法探讨Disinformation的潜在利益、传播动机等具体内涵。结合文献分析总结演化规律并对所预设的7个问题进行系统性回答,就我国Disinformation的概念认知和信息迷雾治理提出建议。

Fake News Classification: Past, Current, and Future

The proliferation of deluding data such as fake news and phony audits on news web journals,online publications,and internet business apps has been aided by the availability of the web,cell phones,and social media.Individuals can quickly fabricate comments and news on social media.The most difficult challenge is determining which news is real or fake.Accordingly,tracking down programmed techniques to recognize fake news online is imperative.With an emphasis on false news,this study presents the evolution of artificial intelligence techniques for detecting spurious social media content.This study shows past,current,and possible methods that can be used in the future for fake news classification.Two different publicly available datasets containing political news are utilized for performing experiments.Sixteen supervised learning algorithms are used,and their results show that conventional Machine Learning(ML)algorithms that were used in the past perform better on shorter text classification.In contrast,the currently used Recurrent Neural Network(RNN)and transformer-based algorithms perform better on longer text.Additionally,a brief comparison of all these techniques is provided,and it concluded that transformers have the potential to revolutionize Natural Language Processing(NLP)methods in the near future.

Domestic Cyberterrorism & Strategic Communications: Literature Review

Cyberterrorism poses a significant threat to the national security of the United States of America (USA), with critical infrastructure, such as commercial facilities, dams, emergency services, food and agriculture, healthcare and public health, and transportation systems virtually at risk. Consequently, this is due primarily to the country’s heavy dependence on computer networks. With both domestic and international terrorists increasingly targeting any vulnerabilities in computer systems and networks, information sharing among security agencies has become critical. Cyberterrorism can be regarded as the purest form of information warfare. This literature review examines cyberterrorism and strategic communications, focusing on domestic cyberterrorism. Notable themes include the meaning of cyberterrorism, how cyberterrorism differs from cybercrime, and the threat posed by cyberterrorism to the USA. Prevention and deterrence of cyberterrorism through information sharing and legislation are also key themes. Finally, gaps in knowledge are identified, and questions warranting additional research are outlined.

Towards Immunizing Infodemic: Comprehensive Study on Assessing the Role of Artificial Intelligence and COVID-19 Pandemic

Artificial Intelligence (AI) technologies have intentionally and unintentionally been used to spread false information on all different types of subjects. Throughout the COVID-19 pandemic, there was a pool of different information that was being presented to the public, a lot of it contradicting one another. False information spreads regardless of whether there is intent to mislead or misinform whereas AI is not able to decipher what type of information it is pushing to the public is correct and what is not. This mass spread of information through online platforms has been coined as an Infodemic where it is considered a massive volume of information, both online and offline. It includes deliberate attempts to disseminate false information to undermine the public health response and advance alternative agendas of groups or individuals. An infodemic can be incredibly dangerous to society greatly affecting the ability of communities, societies, and countries to control and stop the pandemic due to the abundance of different information in combating the health crisis. This article assesses and evaluates the role of Artificial Intelligence (AI) technologies in helping to spread disinformation during the COVID-19 pandemic. It reviews and evaluates the information curation in modern media, the relationship between AI and disinformation, and the challenges of disinformation campaigns. It further outlines the impact of social media platforms on infodemic and their influence in spreading disinformation during the COVID-19 pandemic. This article analyzes several data mining studies that used different machine learning techniques to identify the influence of disinformation tactics on the COVID-19 pandemic associated with the Twitter platform. It further continues exploring the investigation of the number of influential tweets, the type of users, the levels of credibility of URLs, and the type and effect of social media bots. Finally, the authors assess and conclude how disinformation is widely prevalent throughout social media during the COVID-19 pandemic as well as illustrate the surveys that categorize the prevalence of users involved in the conversation about disinformation separated by country including the percentage of users posting tweets and retweeting news URLs, and the future work in combating the rapid disinformation campaigns and their ethical implication impact.