Introduction
With our growing reliance on technology and social media to receive information, identifying disinformation is becoming crucial to orientate in media trends. The striking importance of information literacy became particularly apparent in the age of the global pandemic when disinformation became an immediate threat to people’s health. Identifying fake trends, their origins, and how and why they become widely distributed by people is necessary for navigating today’s media environment. Simultaneously, an alarming growth of disinformation campaigns and their circulation on social media sparks the debate about freedom of speech and highlights the importance of critical thinking and media literacy for contemporary audiences. As information circulates in all spheres of our lives, politics, economy, and healthcare, knowing fake from truth is crucial for everyone who wants to understand and influence the information they consume.
Fake trends on Twitter
Data Collection
Data collection tools can be used to trace the roots of disinformation and ultimately to stunt such activity and to meliorate the toxicity of the media environment. Twitter provides access to its data through its standard application programming interfaces (APIs). However, not all of the APIs offer free unrestricted access. Two of the most commonly used entry points are the Streaming API and the Search API. The Streaming API enables users to perform screening and collect data in real-time. On the other hand, the Search API is used to access older tweets. However, if a researcher needs a sample of data older than seven days, they will have to purchase one of the paid premium plans. Using third-party platforms is one of the alternative options for researchers willing to pay for a friendlier user interface and, in some cases, a wider range of accessible data. Thus, depending on the research and the finances available, one tool can be more useful or appropriate than the other.
Sources of Fake Trends
As a social media platform, Twitter facilitates the dissemination and propagation of information. Some maliciously take advantage of this to create fake trends, while others unknowingly contribute to information manipulation and the spreading of disinformation campaigns and propaganda. Fake trends are popular tendencies with false sources designed to influence public opinion. These ungenuine trends are usually generated through automated bots and suspicious accounts. There are three analytical theories that are commonly used to contain the spread of fake news and prevent them from trending: propagation-based analysis, mathematical modeling based on regression analysis, and user-based analysis. The latter implies a classification of fake-trend sources according to the level of human participation: social bots, cyborgs, and trolls. Although fake news is most widely identified by professional journalists, the vast amounts of information call for more automated methods of identification that incorporate techniques of Information Retrieval, Natural Language Processing (NLP), and Machine Learning. The variety of sources of fake news and the challenges presented by how fast, cheap, and easily accessible information is nowadays condition the use of an eclectic approach when determining the sources.
Examples of Fake Twitter Trends
Fake news usually emerges under the guise of relevant information. Amid the unprecedented global healthcare crisis, news related to the pandemic and vaccination campaigns quickly gained popularity. An example of such a fake trend would be the #5GCoronavirus hashtag that was trending on Twitter in the United Kingdom. While some conspiracies that gave rise to fake Twitter trends tried to find the cause of the virus, others, like the #Filmyourhospital hashtag, denied its existence. This fake trend was encouraging people to believe that the pandemic was a hoax, “proving” it with pictures of empty hospitals. During elections, fake campaigns aiming to change public opinion to one side or another storm social media, igniting debates about whether freedom of speech causes more harm than good. One such fake trend is the #ÇünküÇaldılar hashtag (Because They Stole, implying opposition stole the votes in elections). Many fake trends have a political ax to grind and aim at advancing a certain political agenda. The hashtags “Al Jazeera is the source of lies” and “Al Jazeera insults King Salman” that were trending in Saudi Arabia are examples of fake trends fueling the anti-governmental movements. Fake Twitter trends tend to spread conspiracy theories and promote polarization of public opinions that, in some cases, lead to violence.
Conclusion
Nowadays, the presence of fake trends on social media platforms like Twitter is a common occurrence. Fake news’s purpose is to manipulate mass consciousness in the desired direction. The fakes are usually generated by bots and suspicious accounts. Despite being harmless on the surface, fake trends in media undermine authentic news and information circulation, particularly by causing distrust in people. In some cases, the fakes can be dangerous to a person (as in name theft) or a large group of people (as in fake news related to the COVID-19 pandemic). While there are multiple models and methods used to determine fake trends, people and machines are engaged in analyzing user behavior in consuming and spreading fake information. With the growing percentage and importance of information, people receive online, media literacy and the importance of fact-checking become more apparent to people worldwide.
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