DESIGN AND IMPLEMENTATION OF FAKE NEWS DETECTION SYSTEM USING MACHINE LEARNING ALGORITHM
Fake News” is a term used to represent fabricated news or propaganda comprising misinformation communicated through traditional media channels like print, and television as well as non-traditional media channels like social media. (Thota et al, 2018 ). (Sharma et al, 2007) describes it as the intentional or unintentional spread of false information on public platform. Baptiste et al 2020 seems to veer of from the conceptions of the formers but rather posited that the definition of fake news is shrouded in controversy, with no generally accepted all- encompassing scholarly definition. According to them, the term has been in use since the 19th century but its meaning has undergone several changes over the years, becoming popular in 2016, during the American presidential election campaign. Farkas and Fau, 2008 were of the opinion that the Former U.S President Donald Trump popularized the term during electioneering campaign to label all journalism that did not favour his campaign.
Quoting Menes, 2008, Baptiste et al 2020 explained that since then, the concept of fake news has been repeated in the media context, which has made its meaning more equivocal.
What makes news fake is the source of controversy in defining fake news among scholars. To Menes 2008,, it is the intention to deceive that makes it possible to distinguish between fake news and false news. Conceding to this conception, (Fallis and Mathiesen 2019; Gelfert 2018) posited that The very word “fake” refers us to the intention to deceive and to lie. “Fake” is associated with counterfeiting, imitating the real. False news is not intended to mislead the reader, the false content of a report or piece of news may result from a journalistic error or the journalist’s lack of professionalism in verifying its sources (Nielsen and Graves 2017; Gelfert 2018; Meneses 2018).
(Blokhin and Ilchenko 2015; Levy 2017; Lazer et al. 2018 views fake news from the angle of news authenticity and source credibility, hence they opined that ‘’Fake news seeks to be credible and gain legitimacy by imitating the format of the reports or news, in order to manipulate and deceive the reader and make the fake content look real’’
Fake news can be come in many forms, including: unintentional errors committed by news aggregators, outright false stories, or the stories which are developed to mislead and influence reader’s opinion. While fake news may have multiple forms, the effect that it can have on people, government and organizations may generally be negative since it differs from the facts. It is important to highlight that we approach contemporary fake news, that is, in an online context, in which false statements are widely shared in the digital universe, namely in social media. a. The goal of contemporary fake news is to go viral (Rini 2017; Meneses 2018; Calvert et al. 2018). For these reasons, fake news can take the form of a news feed post (in the case of Facebook) or a tweet (in the case of Twitter), just like the real news is presented on these social media (headline, image, signature/source). In addition, fake news links to sites that mimic real news sites (Silverman 2016).
The idea of fake news is not a novel concept. Notably, the idea has been in existence even before the emergence of the Internet as publishers used false and misleading information to further their interests. Following the advent of the web, more and more consumers began forsaking the traditional media channels used to disseminate information for online platforms .Not only does the latter alternative allow users to access a variety of publications in one sitting, but it is also more convenience and faster. The development, however, came with a redefined concept of fake news as content publishers began using what has come to be commonly referred to as a clickbait.
Clickbaits are phrases that are designed to attract the attention of a user who, upon clicking on the link, is directed to a web page whose content is considerably below their expectations. Many users find clickbaits to be an irritation, and the result is that most of such individuals only end up spending a very short time visiting such sites.
For content publishers, however, more clicks translate into more revenues as the commercial aspect of using online advertisements is highly contingent on web traffic Christopher (2020). As such, despite the concerns that have been raised by readers about the use of clickbaits and the whole idea of publishing misleading information, there has been little effort on the part of content publishers to refrain from doing so.
At best, tech companies such as Google, Facebook, and Twitter have attempted to address this particular concern. However, these efforts have hardly contributed towards solving the problem as the organizations have resorted to denying the individuals associated with such sites the revenue that they would have realized from the increased traffic. Users, on the other hand, continue to deal with sites containing false information and whose involvement tends to affect the reader’s ability to engage with actual news Shiro (2020). The reason behind the involvement of firms such as Facebook in the issue concerning fake news is because the emergence and subsequent development of social media platforms have served to exacerbate the problem Duke (2020). In particular, most of the sites that contain such information also include a sharing option that implores users to disseminate the contents of the web page further. Social networking sites allow for efficient and fast sharing of material and; thus, users can share the misleading information within a short time. In the wake of the data breach of millions of accounts by Cambridge Analytica, Facebook and other giants vowed to do more to stop the spread of fake news .
The project is concerned with identifying a solution that could be used to detect and filter out sites containing fake news for purposes of helping users to avoid being lured by clickbaits. It is imperative that such solutions are identified as they will prove to be useful to both readers and tech companies involved in the issue.
The proposed solution to the issue concerned with fake news includes the use of a tool that can identify and remove fake sites from the results provided to a user by a search engine or a social media news feed. The tool can be downloaded by the user and, subsequently, be appended to the browser or application used to receive news feeds. Once operational, the tool will use various techniques including those related to the syntactic features of a link to determine whether the same should be included as part of the search results.