For lower levels of complexity (readability=6.78), the probabilities for a given text being classified in each category is: factual (p=0.015, CI=[0.013, 0.017]), clickbait (p=0.145, [CI=0.140, 0.149]), conspiracy theories (p=0.160, CI=[0.156, 0.166]), fake news (p=0.373, CI=[0.366, 0.380]), hate speech (p=0.106, CI=[0.102, 0.109]), junk science (p=0.060, CI=[0.058, 0.061]) and rumor (p=0.141, CI=[0.136, 0.147]). In this paper, I propose a model that can differentiate between 7 different categories of content: clickbait, conspiracy theories, fake news, hate speech, junk science, rumors, and finally, factual sources. If so, platforms and fact-checkers can complement their rankings based on virality with rankings based on the probability of a content being non-factual. Secondly, they increase the evidence about structural differences among misinformation types (the breadth challenge), which allows to focus on or differentiate specific categories and create tailored countermeasures for each one. Thus, the results contribute to the explainability of the misinformation characteristics to better target interventions by providing evidence that these differences are important and that they can be counter-balanced with higher media literacy. J Commun 50(1):4670, Lang A (2006) Using the limited capacity model of motivated mediated message processing to design effective cancer communication messages. However, I also report all the other clustering possibilities as a robustness check. CEUR Workshop Proc 718:9398, Pennycook G, Rand D (2017) The implied truth effect: attaching warnings to a subset of fake news stories increases perceived accuracy of stories without warnings. Number one: Declaring war on the press is a high-risk strategy because they have the biggest possible incentive to get you. First, that it is scalable (Broniatowski et al., 2022) and, secondly, misinformation intent is better captured at the source level than at the article level (Grinberg et al., 2019). However, this procedure has a problem: the content is fact-checked once it has gone viral. 98, 2016; Swami, V., et al., Cognition, Vol. Finally, fake news is the category with a lower cognitive effort needed to process the content in all the categories as measured by the readability score (FK=11.25, [CI=11.21, 11.29]). Moreover, another fingerprint of misinformation is its reliance on emotions (Bakir & McStay, 2018; Kramer et al., 2014; Martel et al., 2019; Taddicken & Wolff, 2020). and JavaScript. In presenting the European Democracy Action Plan (EDAP) in 2020, the European Commission pledged to build more resilient democracies across the EU. For example, the word aerospace (low probability) has more information than the or and (high probability). Age. Tumasjan A, Sprenger T, Sandner P, Welpe I (2010) Predicting elections with Twitter: what 140 characters reveal about political sentiment. Political, business or cultural sites that clearly support one position are also suspect. If friends or family share information via
ACM Association for Computing Machinery, Taylor L (2020) Covid-19 misinformation sparks threats and violence against doctors in Latin America. First, although I use a big sample of news articles, these are coming from a selection of websites. Further research is needed to understand the complex interactions between demographic factors such as age and misinformation. Proc Natl Acad Sci USA 114(28):73137318, Article 8, 2020). This resulted in 3177 articles. https://github.com/several, 27, Taddicken M, Wolff L (2020) Fake News in science communication: emotions and strategies of coping with dissonance online. 5Lewandowsky, S., et al. Finally, although we employed widely used dictionaries in the literature, the results are also contingent to the specificities of each dictionary I employed. Why is the Empire the Bad Guys in Star Wars? However, if one opt for explore the results increasing the number of clusters (Fig. On the other hand, intent can vary between mislead the audience (fake news or conspiracy theories), attract website traffic (clickbait) or undefined intent (rumors) (Tables 1 and 2). Here are a few things you might not have known about it. J Lang Soc Psychol 33(4):348377, McLaughlin T (2018) How whatsapp fuels fake news and violence in India. Media literacy organizations such as the News Literacy Project (NLP) and First Draft are applying such strategies in an effort to dispel misinformation and disinformation on COVID-19 and other issues. However, the polarity of these emotions varies across misinformation categories. Appl Soft Comput 97:106754, Article This film discusses some of the reasons the contributions of African and aboriginal people have been left out of the pages of history. Some contemporary approaches. On the other hand, the separations in the first group appear at lower heights (meaning, more similarities among these categories). (Eds. 8, No. Comput Hum Behav 65:567575, Kraft PW, Krupnikov Y, Milita K, Ryan JB, Soroka S (2020) Social media and the changing information environment: sentiment differences in read versus recirculated news content. Next, for the cognitive effort measured through perplexity, one can see that lower levels of perplexity (perplexity=91), the probabilities for a given text being classified in each category is: factual (p=0.001, CI=[0.001, 0.002]), clickbait (p=0.076, CI=[0.073, 0.079]), conspiracy theories (p=0.206, CI=[0.201, 0.212]), fake news (p=0.213, CI=[0.208, 0.218]), hate speech (p=0.216, CI=[0.211, 0.222]), junk science (p=0.049, CI=[0.046, 0.050]) and rumor (p=0.239, CI=[0.235, 0.246]). Focusing on the evolution of traditional media outlets could shed light on the question whether reliable sources are trying to draw on the mechanisms of virality to help increase their penetration (e.g., reliable news becoming more appealing to emotions, titles becoming more exciting, content easier to read, etc.)? Hum Commun Res 47(1):124, Cinelli M, Quattrociocchi W, Galeazzi A, Valensise CM, Brugnoli E, Schmidt AL, Scala A (2020) The COVID-19 social media infodemic. Advances in Experimental Social Psychology, 1, 191229. Adv Exp Soc Psychol 14:159. https://doi.org/10.1177/1077695816651970, Manzoor IS, Singla J, Nikita (2019) Fake news detection using machine learning approaches: a systematic review. Communication and persuasion. 10, No. Mona Sue Weissmark, part-time associate professor of psychiatry and behavioral sciences reflects on the best advice she got:We must learn to live in doubt, yet act based on scientific thinking.. These results indicate that there are significant differences between content characteristics from factual sources and misinformation content in the form of clickbait, conspiracy theories, fake news, hate speech, junk science and rumors. information that can be separated into three distinct types: misinformation, disinformation and mal-information. You are using a browser version with limited support for CSS. But we need to start developing consensus around the facts, says Kasisomayajula Viswanath, Lee Kum Kee Professor of Health Communication. However, prior studies only focus on one or just a few specific categories, usually fake news. This is why I will employ a multinominal logistic regression, a technique suitable for mutually exclusive variables with multiple discrete outcomes. Panelists at the School of Public Health called for a stronger communications effort by physicians to counter misinformation on vaccines. Proc Natl Acad Sci USA 116(16):76767683, de Souza JV, Gomes J, Souza Filho FMde, Oliveira Julio AMde, de Souza JF (2020) A systematic mapping on automatic classification of fake news in social media. The problem with the truth is that it lies in the eye of the beholder and even those that have evidence arent always believed. One of the main reasons proposed to explain this behavior is the dual-process theory of judgment stating that emotional thinking (in contrast to a more analytical thinking) hinders good judgment (Evans, 2003; Stanovich, 2005). WIRED https://www.wired.com/story/how-whatsapp-fuels-fake-news-and-violence-in-india/, Milkman KL, Berger J (2014) The science of sharing and the sharing of science. Proc Assoc Inform Sci Technol 52(1):14, Sagi E, Dehghani M (2014) Measuring moral rhetoric in text. Following the previous example, the string bla bla bla bla bla has a perplexity of 1 (no surprise because all words are the same and, therefore, predicted with a probability of 1), while the string this is an example of higher entropy has a perplexity of 7 (since there are 7 different words that appear 1 time each, yielding a probability of 1-in-7 to appear). Ann Am Acad Polit Soc Sci 658(1):121133, Kramer ADI, Guillory JE, Hancock JT (2014) Experimental evidence of massive-scale emotional contagion through social networks. Official websites for universities, museums or scientific institutes are typically trustworthy, as are websites for federal,
The feasibility of real-time deployment should not be a big problem since this method uses manageable calculations in a reasonable amount of time (less than one second for a 2000 words article). We take this capability for granted because the human brain is. Google Scholar, Kietzmann J, Lee LW, McCarthy IP, Kietzmann TC (2020) Deepfakes: trick or treat? Beyond the title and content for each item, the corpus also categorizes each new into one of the following categories: clickbait, conspiracy theories, fake news, hate speech, junk science, factual sources, and rumors. As for the size of these differences, I showed that fake news are, on average, 18 times more negative than factual news (having hate speech the highest difference with 30 times more negativity than factual news); that factual information is 15% more lexically diverse (with rumors being 19% less diverse than factual news); that fake news appeal to moral values 37% more than factual content (although hate speech appeals 50% more to morality than factual sources); and that fake news are 3% easier to process than factual sources (while fake news are 13% easier to process). The results are the following (Figs. In these situations, misinformation often escalates into violence, like in the case of ethnic brutality in India (McLaughlin, 2018) or violence against doctors in Latin America (Taylor, 2020). The spread of misinformation content is an important and complex problem because not all misleading content is created equal. Take it from the experts, a pet can change your life. Likewise, the results open the door to refining previous research. And misinformation isnt the only factor in hesitancy toward COVID-19 vaccines. When the infodemic struck, van der Linden and Roozenbeek built a new online game, Go Viral!, which aims to prebunk common misinformation surrounding COVID-19. A tendency to see the world as a threatening, nonrandom place without fixed definitions of moralityor to use intuition over analytical thinking when processing informationfurther predicts conspiratorial belief (Moulding, R., et al., Personality and Individual Differences, Vol. Psychologists say that countering misinformation will ultimately require stronger partnerships with social media platforms, which can help disseminate tools such as Go Viral! and provide internal data to researchers studying fake news. To avoid that, one should first click through to the story being shared. In other words, the easier to read a text is, the more likely it pertains to the clickbait, conspiracy theories, fake news, or rumor categories. J Commun 65(4):619638, Bovet A, Makse HA (2019) Influence of fake news in Twitter during the 2016 US presidential election. Soc Netw Anal Mining 7(1):114. A short guide to the history of fake news and disinformation, Why people believe in conspiracy theories, with Karen Douglas, PhD. In general, it is accepted that there are several categories of misinformation delimited by its authenticity and intent. a story to its website saying that police in Nova Scotia were banning drivers from eating breakfast sandwiches. This resulted in the final dataset consisting of 92,112 articles with the following distribution by type: clickbait (12,955 articles), conspiracy theories (15,493 articles), fake news (16,158 articles), hate speech (15,353 articles), junk science (16,252 articles), factual news (1743 articles) and rumors (14,158 articles). Procedure. For example, some fake news sources may use a more neutral tone, while others may show a higher appeal to negative emotions. 13. Thirdly, I propose a method that can be useful to identify misinformation before it becomes viral (the speed challenge), since the categorization of an URL can be done at the exact moment it is posted, allowing for on-spot detection. Also the narrative that the Hidden Colors films feeds into & perpetuates the biologicalization of race, & fact is, race is a social construct. Future Gener Comput Syst 117:4758, Hansen LK, Arvidsson A, Nielsen FA, Colleoni E, Etter M (2011) Good friends, bad news-affect and virality in twitter. In total, the database consists of 213,177 articles. Judgem Decis Making 10(6):549563, Pennycook Gordon, Rand DG (2019) Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. 39, No. Breadth benefits: Not all disinformation is created equal. Facts and truth are matters of life and death.. In general, more advanced and diverse language allows to encode more complex ideas (Ellis & Yuan, 2004), which generates a higher cognitive load (Swabey et al., 2016). This is important because results will indicate how close each misinformation category is to reliable news, allowing us to refine the previously presented results. 12). Next, hate speech separates from conspiracy theories and fake news at height=3.30. This proposal is a highly scalable technique that relies on psychological theories and Natural Language Processing methods to discern between factual news and misinformation types of content. Hidden Colors is a documentary about the real and untold history of people of color around the globe. 15. HIDDEN COLORS 1 Documentary( OUR World's Hi STORY) . For example, Chrysalis Wright, PhD, an associate lecturer and director of the Media and Migration Lab at the University of Central Florida, is studying how misinformation on COVID-19 affects anti-Asian sentiment. From there, I calculate first differences, which are the difference between the two expected, rather than predicted, values (King et al., 2000). 3B), they follow the same behavior as the hierarchical clustering. Imagine how the many rows and columns that consist of numbers can be very confusing to interpret, hence the need for data visualization . 3. Google Scholar, Guess AM, Lerner M, Lyons B, Montgomery JM, Nyhan B, Reifler J, Sircar N (2020) A digital media literacy intervention increases discernment between mainstream and false news in the United States and India. However, not all misinformation is created equal. The Shorenstein Centers News Sustainability program produces original research on sustainable business models for the digital age, and works closely with legacy and emerging news organizations to put the theories into practice creating a cycle of research, implementation, and learning. The results show that a one-unit increase in the readability score is associated with a decrease in the log odds of categorizing content in the clickbait (\(\beta _{{\mathrm{readability}},\,{\mathrm{clickbait}}} = - 0.06\), p<0.001) conspiracy theories (\(\beta _{{\mathrm{readability}},\,{\mathrm{conspiracy}}} = - 0.05\), p<0.001), fake news (\(\beta _{{\mathrm{readability}},\,{\mathrm{fake}}\,{\mathrm{news}}} = - 0.21\), p<0.001), and rumor (\(\beta _{{\mathrm{readability}},\,{\mathrm{rumor}}} = - 0.04\), p<0.001) categories. 4. (1999); Consciousness and Cognition, 8(3), 338342; Pennycook, G., & Rand, D. G. (2019). Beyond the small effect, these systems rely on content or sources that have already been flagged as potential misinformation. PLoS ONE 10(2):e0118093, Article Tell us what's wrong with this post? The dictionary contains 411 words like abomination, demon, honor, infidelity, patriot or wicked. 7, No. Technol Soc 13:259278, Swabey L, Nicodemus B, Taylor MM, Gile D (2016) Lexical decisions and related cognitive issues in spoken and signed language interpreting. spread. Just because people know how to fact-check doesnt guarantee theyll do it in the right context. Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence. B darker colors indicate stronger associations. Consider if your own beliefs could affect your judgement. Read more from the Harvard Chan School of Public Health, Watch the Harvard Institute for Applied Computational Science video. Stare at the dot for 30-45 seconds. The film discusses the role of African and aboriginal people in history and argues some achievements have not been properly recorded or credited to them. Can You Blame Game of Thrones EPs for Skipping Comic Con? The photo of Singh and those of the mansion were real, but he did not own the home; it is a rental property in the United States. This is important because this type of model have been rarely available (Miller et al., 2017). Graduate School of Arts and Sciences named in honor of alums four decades of philanthropy, support for expanding opportunity, advancing excellence. 31, No. Research the site and author to be sure. Total price: $83.08. Sources that are well-known promoters of kooky conspiracy theories. A Clustering results with two clusters. Learning how to separate facts from misinformation or so-called fake news has become a critical modern skill as people
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