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Purpose In March 2019, Facebook updated its security procedures requesting ID verification for people who wish to advertise or promote political posts of adverts. The announcement received little media coverage even though it is an interesting development in the battle against fake news. This paper aims to review the current literature on different approaches in the battle against the spread of fake news, including the use of computer algorithms, artificial intelligence (AI) and introduction of ID checks. Design/methodology/approach Critical to the evaluation is consideration into ID checks as a means to combat the spread of fake news. To understand the process and how it works, the team undertook a social experiment combined with reflective analysis to better understand the impact of ID check policies when combined with other standards policies of a typical platform. Findings The analysis identifies grave concerns. In a wider context, standardising such policy will leave political activists in countries vulnerable to reprisal from authoritarian regimes. Other victims of the impacts include people who use fake names to protect the identity of adopted children or to protect anonymity from abusive partners. Originality/value The analysis also points to the fact that troll armies could bypass these checks rendering the use of ID checks less effective in the battle to combat fake news.

Several researchers have attempted to investigate the processes that govern and support the spread of fake news. This paper collates and identifies these variables. The paper then categorizes these variables based on three key players that are involved in the process: Users, Content, and Social Networks. To complete this task, the authors conducted an extensive review of the literature and a reflection on the key variables that are involved in the process. The paper has identified a total of twenty-seven variables. Then the paper presents a series of tasks to mitigate or eliminate these variables in a holistic process that could be automated to reduce or eliminate fake news propagation. Finally, the paper suggests further research into testing the method in lab conditions.

Social media is becoming the de-facto platform for the dissemination of information as research suggests more Internet users are using social media as their main source of news. In this model, the spread of unverified information is becoming a common place where some could share misinformation as fact. News sharing on social media lacks the traditional verification methods used by professional media. In previous publications, the authors presented a model that shows the extent of the problem thus suggesting the design of a tool that could assist users to authenticate information using a conceptual approached called ‘right-click authenticate’ button. A two-dimensional simulation provided bases for a proof-of-concept and identification of key variables. This paper uses Biolayout three-dimensional modelling to expand their simulations of different scenarios. Using the given variables and values, this paper presents a better understanding of how misinformation travels in the spatial space of social media. The findings further confirmed that the approach of ‘right-click authenticate’ button would dramatically cut back the spread of misinformation online.

Academic research shows increase reliance of online users on social media as a main source of news and information. Researchers found that young users are particularly inclined to believe what they read on social media without adequate verification of the information. There has been some research to study the spread of misinformation and identification of key variables in developing simulations of the process. Current literature on combating misinformation focuses on individuals and neglects social newsgroups-key players in the dissemination of information online. Using benchmark variables and values from the literature, the authors simulated the process using Biolayout; a big data-modeling tool. The results show social newsgroups have significant impact in the explosion of misinformation as well as combating misinformation. The outcome has helped better understand and visualize how misinformation travels in the spatial space of social media.

One of the key features of social networks is that users are able to share information, and through cascades of sharing information, this information may reach a large number of individuals. The high availability of user-provided contents on online social media facilitates people aggregation around shared beliefs, interests, worldviews and narratives. With lack of means to verify information, social media has been accused of becoming a hot bed for sharing of misinformation. Facebook, as one of the largest social networking services, has been facing widespread criticism on how its newsfeed algorithm is designed thus amplifying dissemination of misinformation. In late 2016, Facebook revealed plans to address fake news on Facebook newsfeeds. In this work, we study the methods Facebook has proposed to combat the spread of misinformation and compare it with our previously proposed approach called ‘Right-click Authenticate’. By analyzing the Business Process Modeling and Notation of both approaches, this paper suggests some key weaknesses and improvements social media companies need to consider when tackling the spread of misinformation online.

The spread of misinformation online is specifically amplified by use of social media, yet the tools for allowing online users to authenticate text and images are available though not easily accessible. The authors challenge this view suggesting that corporations’ responsible for the development of browsers and social media websites need to incorporate such tools to combat the spread of misinformation. As a step stone towards developing a formula for simulating spread of misinformation, the authors ran theoretical simulations which demonstrate the unchallenged spread of misinformation which users are left to authenticate on their own, as opposed to providing the users means to authenticate such material. The team simulates five scenarios that gradually get complicated as variables are identified and added to the model. The results demonstrate a simulation of the process as proof-of-concept as well as identification of the key variables that influence the spread and combat of misinformation online.