Dance, William

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Science in Parliament  |  Vol 75 No 3  |  Autumn 201920DISINFORMATION ONLINE: SOCIAL MEDIA USER’S MOTIVATIONS FOR SHARING ‘FAKE NEWS’ In line with the recommendation of the Digital, Culture, Media and Sport Committee (1), this article will use the term disinformation and not fake news.William Dance, UKRI NWCDTP PhD Student and Associate Lecturer, Lancaster UniversityWHAT IS DISINFORMATION? Disinformation is a global issue – it is language agnostic and can be published for political, social, financial or other gain. It can be seemingly innocuous without any apparent target or it can constitute abusive content directed at particular groups. Despite its prevalence and potential for harm, it is also often misunderstood. Disinformation is: intentionally factually incorrect news that is published to deceive and misinform its reader. This is contrasted to misinformation – the unintentional sharing of false information. Usually disinformation is intentionally broadcast by the producer and misinformation is that same content unintentionally shared by the reader. Disinformation differs from satire and parody because it endeavours to appear factual and sincere, though when poorly executed or hastily read, satire and parody may inadvertently be mistaken for truth. And though the concept – or its name – may feel new, it is a very old phenomenon. This can be shown by searching for terms such as disinformation, misinformation and fake news in large, historic databases of language. While the main terms used today are the three listed above, the most common term previously was false news: Example  Year      Use 1            1534    that from henceforth none be so hardy to tell or publyshe any false news or saes whereby discord or ccsyon or dyscord or sklaunder may gw 2            1661    I. Innovations in Government ; Publishing of false News, and Prophesies ; Pretenses of Reformation ; Sects and Divisions in matters of Religion ; Quarrel against Episcopacy  3            1689    the King put out a Proclamation , prohibiting the spreading of Rumours and False News.  Disinformation has also been the subject of much discussion for over 300 years: Example  Year      Use 4           2019    Why is there so much “Fake News” in this age of information 5             2017    Why make fake news up? 6            1692    What is the reason there is so much false news spread abroad, and that many delight to make others believe strange things?  The examples above show two tweets alongside writing from 1692, all posing the same question: why do people read and share disinformation? Some research has looked at political belief and the likelihood of sharing disinformation (2) while in the UK, Loughborough University’s O3C research group administered a UK survey to answer these questions (3). However, to understand why people share disinformation it is important to look at the precise moment it is shared: the point at which a reader becomes a sharer. By exploring this moment, we can identify the motives, rationales, and beliefs behind (unwittingly) sharing disinformation. One exploratory method is to analyse social media posts that link to false content. Exploring what people write when they share false content can show why they shared it to begin with, and this is precisely what was done for section 3 of this article. For example: Science in Parliament  |  Vol 75 No 3  |  Autumn 2019 21In the example above, as in section 3 below, the yellow text is collected into a dataset, while the green information is not. This was done for a total of 10,743 tweets totalling 174,875 words. All the false articles linked to in these tweets were manually fact checked. 2. METHOD To explore large quantities of naturally occurring language data like this, a method was needed that can process thousands of tweets (i.e. words) to produce coherent results. The method used was ‘corpus linguistics’. From the Latin corpus (literally: body), corpus linguistics uses computers to explore linguistic patterns in large collections (or ‘bodies’) of language. However, looking at single words or phrases may mean that some words are accidentally overlooked, thus an approach was chosen that grouped similar words – that is, words in the same semantic domain – together. A semantic domain can be as fundamental as ‘words denoting science’ or as fine grained as ‘words denoting clothes and personal belongings’. The online tool, Wmatrix (4) developed at Lancaster University, was used to automatically assign semantic domains to words. Wmatrix draws on its USAS tag set, which contains 232 semantic categories (5) and this allowed similar words from the corpus to be grouped and analysed together. 3. WHY DO PEOPLE SHARE DISINFORMATION? To investigate the characteristics of disinformation sharing, a larger non-disinformation dataset was collected. This corpus comprised shared news links irrespective of veracity and functioned as a benchmark. By comparing the two corpora (disinformation vs non-disinformation), the features that are unique to disinformation sharing can be revealed. This method, known as keyness analysis, reveals items are that statistically significant, also known as statistically ‘key’. This means the items occur beyond that of chance – for this study, the threshold was a less than one chance in a thousand of items being mislabelled as key (p. <0.0001). The most key semantic domain in the disinformation-sharing corpus was A10- Closed; Hiding/Hidden. This domain comprises terms relating to a level of concealment, and from the corpus the following instances occurred:  Uses cover up; hiding; anon; classified; secret; burying; disappears; concealed; disguised; secret_society  The words all relate to information being hidden or secret, with uses such as cover up and concealed. One possible explanation for these words appearing so often is that poverty of knowledge can contribute to falling victim to deception (6). In this sense, people rely on news to provide the knowledge they lack and stories that were hidden or concealed may be more enticing not only because they claim to provide new information, but because that information is supposedly being withheld, and must therefore be important. If one’s goal is to obtain new information, it is logical to read articles that purport to contain exactly this. Similarly, allusions to classified and cover up can tap into and capitalise on distrust and conspiratorial belief. Interestingly, the domain opposite to A10 - is also used unusually frequently in the disinformation sharing corpus. A10+ Open; Finding; Showing comprises terms relating to openness and exposure: Uses show; find; reveals; discovered; exposes; open; revealed; uncovers  By its very nature, disinformation is the revelation of fabricated “facts” previously unknown to anyone besides the author. As a result, those who believe and share that disinformation are likely to mention that it reveals and exposes and uncovers. Together, these two domains, A10- and A10+, show how people read and share disinformation because they view it as exposing and revealing news that is secret or hidden. Another key domain is A5.2- Evaluation: False – words depicting (a lack of) truth: Uses lies; liars; disingenuous; nonsense; false; charade; deception; kidding; telling_lies; fabricated; misleading; fiction; crafty  This finding is not necessarily surprising. The prevalence of disinformation has been attributed to the notion of a post-truth society (7) and has been labelled as an “information crisis” (8). Similarly, research has noted that “the declining trust in mainstream media could be both a cause and a consequence of fake news gaining more traction” (Allcott and Gentzkow, 2017, p. 215). In this sense, low trust in institutions is compounded by disinformation which capitalises on this distrust. This is backed up by research that shows trust, both off and on social media, is decreasing in the global north (Reuters, 2018). A similar domain that is key is O4.2- Negative Judgement of Appearance – these are terms relating to unpleasant general appearance and physical properties: Uses nasty; disgusting; vulgar; horrible; despicable; trashy; tasteless; vile; awful; tainted; soul-less  These uses show a clear sentiment: anger. That words denoting anger are statistically key in the sharing of disinformation shows that there is an important emotional element involved. A strong emotional response may well correlate with a reduced critical ability to spot falsehoods, thereby increasing the likelihood of unwittingly sharing false news – successful disinformation organisations are almost certainly aware of this. However, anger and negative response are not the only emotions at play. The domain A13.3 Degree Boosters is also key. This domain comprises words such as intensifiers that amplify to a higher (but not the highest) degree: Uses really; more; very; so; such_a; far; extremely; as_hell; awfully; heavily; seriously; particularly  Science in Parliament  |  Vol 75 No 3  |  Autumn 201922However, not all these terms are used negatively. Some uses in the data are:  Example Use 7 Leave it to the trolls to stoop to this, and much worse 8 Something is seriously wrong with the #DOJ 9 Also a very good sign this is another false flag 10 David HOGG has been astonishingly articulate &; highly skilled at spreading a new narrative  The latter two uses above, very good and astonishingly articulate, exhibit a positive sentiment. This shows that these disinformation articles not only target emotion but are shared by people who are passionate and feel the need to use descriptors such as very and really much more commonly than non-disinformation news sharing. This is similar to the emotional investment seen with the negative judgements. 4. WHAT DOES ALL OF THIS MEAN? A recurring theme in the examples above is truth. Whether this is social media users saying articles are revealing the truth or users accusing others of being disingenuous or fake, these results show that disinformation is an issue of truth. Further, declining trust creates the ideal conditions for disinformation which in turn creates a cycle of decreasing truth. People are also passionate in their news sharing. Those sharing disinformation modify their posts with words like extremely and very more than those who share legitimate information. This suggests that our emotions potentially compromise our critical faculties, making us vulnerable to disinformation. 5. CONCLUSION: HOW WE TALK ABOUT DISINFORMATION MATTERS. Disinformation is a multifaceted, complex issue. It is partly a media literacy issue, but it can also be caused, or exacerbated, by declining trust, socio-political beliefs, or an interplay of these and other factors. One aspect that is clear is that how we talk about disinformation matters. Language is “socially constitutive as well as socially conditioned” (Fairclough and Wodak, 1997, p, 258) in that social situations can govern and be governed by the very language we use. The term ‘fake news’ itself is problematic due to its use as an insult, and although disinformation can be light-hearted such as with sensationalist clickbait, it also has the pernicious ability to damage social cohesion and target vulnerable groups. How we discuss the issues of fake news, disinformation, and misinformation will determine how effective we can be in dealing with it and it should be treated as the far-reaching issue it is. References: (1)  House of Commons Digital, Culture, Media and Sport Committee Disinformation and ‘fake news’: Final Report Eighth Report of Session 2017–19. Available here: https://publications.parliament.uk/pa/cm201719/cmselect/cmcumeds/1791/1791.pdf (2)  Guess, A., Nagler, J., & Tucker, J. (2019). Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Science advances, 5(1). Available here: https://advances.sciencemag.org/content/5/1/eaau4586 (3)   Chadwick, A., & Vaccari, C. (2019). News sharing on UK social media: Misinformation, disinformation, and correction. Available here: https://www.lboro.ac.uk/media/media/research/o3c/Chadwick%20Vaccari%20O3C-1%20News%20Sharing%20on%20UK%20Social%20Media.pdf (4)   Rayson, P. (2009) Wmatrix: a web-based corpus processing environment, Computing Department, Lancaster University. http://ucrel.lancs.ac.uk/wmatrix/. (5)   Archer, D., Wilson, A and Rayson, P. (2002). Introduction to the USAS category system. Available here: http://ucrel.lancs.ac.uk/usas/usas_guide.pdf. (6)   Urchs, M. (2007) The logic of lying. In J. Mecke (ed.) Cultures of lying: Theories and practice of lying in society, literature and film. Berlin: Galda + Wilch Verlag. Pp. 21-46. (7)   Flood, A and The Guardian. (2016). 'Post-truth' named word of the year by Oxford Dictionaries. Available here: https://www.theguardian.com/books/ 2016/nov/15/post-truth-named-word-of-the-year-by-oxford-dictionaries. (8)   London School of Economics and Political Science. (2018). Tackling the Information Crisis: A Policy Framework for Media System Resilience. Available here: http://www.lse.ac.uk/media-and-communications/assets/documents/ research/T3-Report-Tackling-the-Information-Crisis.pdf. 

Disinformation online:Social media user’s motivations for sharing ‘fake news’

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