}}{{P\left( {{\mathrm{cat}} = J = {\mathrm{reliable}}} \right)}}} \right) = \beta _{0j} + \beta _{1j}\left( r \right) + \beta _{1j}\left( p \right) + \beta _{1j}\left( s \right) + \beta _{1j}\left( m \right)$$, \(\beta _{{\mathrm{readability}},\,{\mathrm{clickbait}}} = - 0.06\), \(\beta _{{\mathrm{readability}},\,{\mathrm{conspiracy}}} = - 0.05\), \(\beta _{{\mathrm{readability}},\,{\mathrm{fake}}\,{\mathrm{news}}} = - 0.21\), \(\beta _{{\mathrm{readability}},\,{\mathrm{rumor}}} = - 0.04\), \(\beta _{{\mathrm{readability}},\,{\mathrm{hate}}} = 0.01\), \(\beta _{{\mathrm{readability}},\,{\mathrm{junk}}\,{\mathrm{science}}} = 0.04\), \(\beta _{{\mathrm{perplexity}},\,{\mathrm{clickbait}}} = - 0.03\), \(\beta _{{\mathrm{perplexity}},\,{\mathrm{conspiracy}}} = - 0.04\), \(\beta _{{\mathrm{perplexity}},\,{\mathrm{fake}}\,{\mathrm{news}}} = - 0.04\), \(\beta _{{\mathrm{perplexity}},\,{\mathrm{hate}}} = - 0.04\), \(\beta _{{\mathrm{perplexity}},\,{\mathrm{junk}}\,{\mathrm{science}}} = - 0.01\), \(\beta _{{\mathrm{sentiment}},\,{\mathrm{clickbait}}} = - 0.01\), \(\beta _{{\mathrm{sentiment}},\,{\mathrm{conspiracy}}} = - 0.02\), \(\beta _{{\mathrm{sentiment}},{\mathrm{fake}}\,{\mathrm{news}}} = - 0.02\), \(\beta _{{\mathrm{sentiment}},{\mathrm{hate}}} = - 0.03\), \(\beta _{{\mathrm{sentiment}},{\mathrm{junk}}\,{\mathrm{science}}} = 0.02\), \(\beta _{{\mathrm{sentiment}},\,{\mathrm{rumor}}} = 0.01\), \(\beta _{{\mathrm{morality}},\,{\mathrm{clickbait}}} = 0.18\), \(\beta _{{\mathrm{morality}},\,{\mathrm{conspiracy}}} = 0.18\), \(\beta _{{\mathrm{morality}},\,{\mathrm{fake}}\,{\mathrm{news}}} = 0.20\), \(\beta _{{\mathrm{morality}},\,{\mathrm{hate}}} = 0.16\), \(\beta _{{\mathrm{morality}},\,{\mathrm{junk}}\,{\mathrm{science}}} = 0.16\), \(\beta _{{\mathrm{morality}},\,{\mathrm{conspiracy}}} = 0.14\), \({\mathrm{Readability}} = \left[ {6.78,\,22.05} \right]\), \({\mathrm{Perplexity}} = \left[ {91.37,\,215.01} \right]\), \({\mathrm{Sentiment}} = \left[ { - 32,\,28} \right]\), https://doi.org/10.1057/s41599-022-01174-9, Humanities and Social Sciences Communications (, ChatGPTs inconsistent moral advice influences users judgment, Evidence of a predictive coding hierarchy in the human brain listening to speech, Supernatural explanations across 114 societies are more common for natural than social phenomena, The psychological drivers of misinformation belief and its resistance to correction, Overperception of moral outrage in online social networks inflates beliefs about intergroup hostility, Negativity drives online news consumption, Artificial intelligence in communication impacts language and social relationships, A cross-verified database of notable people, 3500BC-2018AD, The use-the-best heuristic facilitates deception detection, Information systems and information technology, https://github.com/several27/FakeNewsCorpus, https://ieeexplore.ieee.org/abstract/document/6234430, https://www.wired.com/story/how-whatsapp-fuels-fake-news-and-violence-in-india/, https://github.com/BigMcLargeHuge/opensources, http://creativecommons.org/licenses/by/4.0/, What to believe? interview with a witness, an account that turned out to be wrong. Some of the prominent social media platforms have intended to stop the proliferation of misinformation with different features like relying on users reporting mechanisms (Chan et al., 2017; Lewandowsky et al., 2012) or using fact-checkers to analyze content that already went viral through the network (Chung & Kim, 2021; Tambuscio et al., 2018; Tambuscio et al., 2015). Afroz S, Brennan M, Greenstadt R (2012) Detecting hoaxes, frauds, and deception in writing style online. 2, 2017; Jolley, D., & Douglas, K. M., Journal of Applied Social Psychology, Vol. In general, content that evokes high-arousal emotions is more viral (Berger, 2011; Berger & Milkman, 2009; Berger & Milkman, 2013; Goel et al., 2015; Milkman & Berger, 2014), which explains why social networks are a source of massive-scale emotional contagion (Fowler & Christakis, 2009; Kramer et al., 2014; Rosenquistet al., 2011). In total, the database consists of 213,177 articles. Here are some tips to help you tell fact from fiction in todays news. This is aligned with the call for public interest algorithms to identify misinformation and protect consumers (Wheeler, 2017). Lewandowsky, Schwarz, van der Linden, and others have shown that prebunking can neutralize misinformation on climate change, vaccines, and other issues (Global Challenges, Vol. Cailin OConnor and James Owen Weatherall. In essence the films are about the accomplishment of the African peoples and how its been re-discovered by those that knew where to look. Using hidden cameras, social media, court documents and tax returns, Marketplace pieced together a portrait of the movement's misinformation and fundraising tactics. (Eds. Pew Research Center, 12, Singh L, Bode L, Budak C, Kawintiranon K, Padden C, Vraga E (2020) Understanding high- and low-quality URL Sharing on COVID-19 Twitter streams. To my knowledge, this is the paper with higher number of categories and higher number of news articles. This is especially relevant for people with low levels of media literacy (Lazer et al., 2018) because the results show that, in general, misinformation requires less cognitive effort for being processed and is more reliant on emotions than factual information: it is easier to read, and falsified content creators use a less diverse vocabulary, which may explain why misinformation is more prevalent among low-literacy individuals (Lazer et al., 2018), and more appealing to negative emotions and moral values, which may influence our ability to discern between misinformation and factual content. This seems like a very large claim and one that Asians might very well dispute but for the fact that there seem to be some solid facts leading up to it. Ssrn 49(2):192205, Berger J, Milkman KL (2013) Emotion and virality: what makes online content go viral? SAGE Publications, Sage CA: Los Angeles, CA, Fuller CM, Biros DP, Wilson RL (2009) Decision support for determining veracity via linguistic-based cues. This method will allow us, beyond the fingerprints of misinformation described before, to quantify the differences between factual news and non-factual content. But we need to start developing consensus around the facts, says Kasisomayajula Viswanath, Lee Kum Kee Professor of Health Communication. 3B), they follow the same behavior as the hierarchical clustering. Moreover, the results must be interpreted in the light of some methodological limitations that I expose in the corresponding section. Google Scholar, Broniatowski DA, Kerchner D, Farooq F, Huang X, Jamison AM, Dredze M, Ayers JW (2022) Twitter and Facebook posts about COVID-19 are less likely to spread misinformation compared to other health topics. Thank you for visiting nature.com. Then, I change the value of the variable to its ending point (high range), keeping all the other variables at their means and repeat the simulation. The 197 websites hosting the 92,112 articles are: In comparison to other datasets, the one used in this paper includes more sources and more articles than any other: Extant research in the human cognition and behavioral sciences can be leveraged to identify misinformation online through quantitative measures. The author declares no competing interests. Am J Polit Sci 44(2):347, Koenecke A, Nam A, Lake E, Nudell J, Quartey M, Mengesha Z, Goel S (2020) Racial disparities in automated speech recognition. Further research is needed to understand the complex interactions between demographic factors such as age and misinformation. Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. This logistic model is generalizable to categorical variables with more than two levels namely {1,,J}{1,,J}. And misinformation isnt the only factor in hesitancy toward COVID-19 vaccines. Theres often a lot of uncertainty in crisis situations, so people come together and start sharing information in a sort of collective sense-making process, says Kate Starbird, PhD, an associate professor of human-centered design and engineering at the University of Washington, who studies how information travels during crises. But psychologists who study fake news warn that its an uphill battle, one that will ultimately require a global cooperative effort among researchers, governments, and social media platforms. Professionally curated lists of online sources, available free for public use. After three clusters, reliable news is the first category to be isolated from all the others, revealing its distinctive nature in terms of linguistic characteristics. Hidden Colors is a documentary about the real and untold history of people of color around the globe. 263, 2020). Although there is little research on how moral content contributes to online virality (Rathje et al., 2021), the mechanism is grounded in social identity theory (Tajfel & Turner, 1979) and self-categorization theory (Turner et al., 1987) and lies in the idea that group identities are hyper salient on social media (Brady et al., 2017) because they act as a form of self-conscious identity representation (Kraft et al., 2020; van Dijck, 2013). Misinformation is a type of fake news, which is false information reported by media outlets or shared by regular people. PsycNET. Thought processes more common among those who hold far-right political beliefs, such as paranoid ideation and distrust of authority, also correlate with an increased endorsement of conspiratorial narratives (van Prooijen, J.-W., et al., Social Psychology and Personality Science, Vol. Sci Rep 2020 10:1 10(1):110, Cox RH, Dickson D, Marier P (2020) Resistance, innovation, and improvisation: comparing the responses of nursing home workers to the COVID-19 pandemic in Canada and the United States. If you said brown, then you're wrong. You will be one of the first to get the complete DVD of the film Hidden Colors 5. Cabinet Office, the WHO, and the United Nations, the game has already reached thousands of people. How would you rate this article? Those that believe that people color have a vendetta against those living in the current world would be among the first to state that the documentary is horribly skewed to one side and might attempt to discredit it. ADS Google Scholar, Brady WJ, Crockett MJ, Van Bavel JJ (2020) The MAD model of moral contagion: the role of motivation, attention, and design in the spread of moralized content online. We want people to understand that disinformation is fundamentally exploitativethat it tries to use our religion, our patriotism, and our desire for justice to outrage us and to dupe us into faulty reasoning, says Peter Adams, NLPs senior vice president of education. DVD. J Commun 65(4):699719, Wheeler T (2017) Using public interest algorithms to tackle the problems created by social media algorithms, Zervopoulos A, Alvanou AG, Bezas K, Papamichail A, Maragoudakis M, Kermanidis K (2020) Hong Kong protests: using natural language processing for fake news detection on twitter. I repeat this process 100 times and average the results for the starting and ending points. an unbelievable amount of blustery hooplaw that is not only factually incorrect but painfully shallow and excruciatingly reaching, whats so sad about . For example, a text containing the string bla bla bla bla bla has an entropy of 0 because p(bla)=1 (a certainty), while the string this is an example of higher entropy has an entropy of 2.807355 (higher uncertainty). For example, encouraging people to think analytically, in contrast to emotionally, decreases likelihood of liking or sharing fake news (Effron & Raj, 2020). PLoS ONE 13(10):e0203794, Helmstetter S, Paulheim H (2018) Weakly supervised learning for fake news detection on Twitter. Therefore, it is not enough to report the averages and confidence intervals of each variable for each category, but also analyzing differences and similarities in the light of all variables altogether. First differences of the multinominal logit modelPerplexity. For example, the WHO lists Go Viral! as a resource for tackling online misinformation and has featured the game in its newsletters. 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. 5. Psychological research has shown that peoples memories can be made wrong by information they learn after the event theyre recalling. "Misinformation in Canada.". J Commun 65(4):619638, Bovet A, Makse HA (2019) Influence of fake news in Twitter during the 2016 US presidential election. To do so, I calculate a set of quantifiable characteristics that represent the content of a written text and allow us to differentiate it across categories. Washington, DC, USA, May 2326, 2010, Turner J, Hogg M, Oakes P, Reicher S, Wetherell M (1987) Rediscovering the social group: a self-categorization theory. IEEE Comput Intell Magaz 15(1):6475, Article 47, No. The challenges of educating the public about a deadly pandemic while also dealing with an outbreak of misinformation. Harvard expert Fran Berman advocates for prioritizing public interest over profit with tech innovation and social and regulatory controls. Through partnerships with the U.K. This item: Hidden Colors Part 1, 2 & 3 - Brand NEW. 188, 2019). The second in the series, Hidden Colors 2: The Triumph of Melanin, was released the following year on December 6, 2012. In order to carry out the analysis I use the Fake News Corpus (Szpakowski, 2018), comprised of 9.4 million news items extracted from 194 webpages. First, they contribute to diminish the problem of scalability in misinformation detection (the volume challenge), by providing a set of features that can differentiate between misinformation and factual content without human intervention. 5.0 . First, although I use a big sample of news articles, these are coming from a selection of websites. But I can. For decades, the fossil fuel industry has poured millions of dollars into spreading climate disinformation[1] online and offline to drive public polarization and stall action on the climate crisis. Proc Assoc Inform Sci Technol 52(1):14, Sagi E, Dehghani M (2014) Measuring moral rhetoric in text. PubMed Online social networks meet several of the criteria known by psychologists to make statements persuasive. This is not an optical illusion, but rather color adaptation of the eye. In this type of problem, each text in a set of news articles can be represented as a set of k features denoted by the feature vector \(f \in {\Bbb R}^k\). 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). December. 4, 2020). Here are a few things you might not have known about it. International Center for Journalists. For example, the Pew Research Center found that only 17% of US adults have the skills to safely navigate the information ecosystem (Horrigan, 2016). Such falsehoods, which research shows have influenced attitudes and behaviors around protective measures such as mask-wearing, are an ongoing hurdle as countries around the world struggle to get the virus under control. The objective was not to provide the most detailed model to describe misinformation, but a parsimonious description of key features. Psychol Scie Public Interest, Suppl 13(3):106131, Liu Z, Park S (2015) What makes a useful online review? $54.53. 7, No. Misinformation: Spreading false information (rumors, insults, and pranks). Regarding cognitive effort, extant research in the human cognition and behavioral sciences can be leveraged to identify misinformation through quantitative measures. However, I also report all the other clustering possibilities as a robustness check. CAS Do a quick search on the author. PubMed Central Thanks for reading! In this case, I am interested in the determination of the emotional state (positive, negative, or neutral) that the text tries to convey towards the reader. Proc Natl Acad Sci USA 106(41):1728417289, Article https://doi.org/10.1177/2053168019848554, Appelman A, Sundar SS (2016) Measuring message credibility: construction and validation of an exclusive scale. Stud Second Lang Acquis 26(1):5984, Eshet Y, Eshet Y (2004) Digital literacy: a conceptual framework for survival skills in the digital era. 2016 Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media, 4(1). The spread of misinformation content is an important and complex problem because not all misleading content is created equal. Researchers also observed that beliefs persist even after misinformation is corrected and began to test interventions for resisting persuasion.2, 1990s2000s Infodemic: World Health Organization defines an infodemic as "an overabundance of informationsome accurate and some notthat . However, the polarity of these emotions varies across misinformation categories. Dont they know how contagious this virus is? PubMed Central Its Vis. Starting in the 1970s, psychologists showed that even after misinformation is corrected, false beliefs can still persist (Anderson, C. A., et al., Journal of Personality and Social Psychology, Vol. The lead author of one such analysis, Gordon Pennycook, PhD, an assistant professor of psychology at the University of Regina in Saskatchewan, Canada, says this suggests that passive sharers, rather than malicious actors, may be the bigger problem in the fake news phenomenon (Cognition, Vol. Learning at Harvard can happen for every type of learner, at any phase of life. Naval Technical Training Command Millington TN Research Branch, King G, Tomz M, Wittenberg J (2000) Making the most of statistical analyses: improving interpretation and presentation. The obtained results offer the opportunity to explore to what extent different misinformation categories are more viral than others and how their structural features in terms of cognitive effort and appeal to emotions drive this virality. Get tickets to our next game, hours and locations for our libraries and museums, and information about your next career move. Since it is impossible to check everything that is being shared on social media, fact-checkers focus on content that has already become viral (usually, with information provided from social media platforms in the form of rankings). A test of COVID-19 misinformation led by Pennycook and his colleagues found that a simple accuracy nudge increased participants ability to discern between real and fake news. Watch Think Dig Deeper Customize this lesson 1021 Create and share a new lesson based on this one. This is important because views and engagement in social networks are closely related to virality, and being repeatedly exposed to misinformation increases the likelihood of believing in false claims (Bessi et al., 2015; Mocanu et al., 2015). B Clustering results with more than two clusters. However, prior studies only focus on one or just a few specific categories, usually fake news. In contrast to previous measures, the technique employed to quantify morality is highly sensitive to text length (with longer texts having higher probabilities of containing moral words), therefore, I calculate the morality measure as moral words per 500 words in each text. Regarding first differences, one can see that increasing the readability score from 6.78 to 22 has no effect on the probabilities of content being classified as factual news (p=0.000, CI=[0.003, 0.003]), decrease by 6.44% the probabilities of being clickbait (CI=[0.074, 0.056]), a decrease of 5.16% for conspiracy theories (CI=[0.061, 0.042]), or a decrease of 3.47% in rumors (CI=[0.044, 0.026]); remarkably, increasing the readability translates into a decrease of 35% of being classified as fake news (CI=[0.361, 0.344]). Soc Netw Anal Mining 10(1):121, Dehghani M, Johnson K, Hoover J, Sagi E, Garten J, Parmar N, Graham J (2016) Purity homophily in social networks. Lewandowsky, S., et al., 2020, Coronavirus misinformation: Quantifying sources and themes in the COVID-19 infodemic example, participants in one study were shown video of a car accident. J Broadcast Electron Media 54(3):485507, Lewandowsky S, Ecker UKH, Seifert CM, Schwarz N, Cook J (2012) Misinformation and its correction: continued influence and successful debiasing. 16, No. Whoif anyoneshould stop it? Google Scholar, Barrn-Cedeo A, Jaradat I, Da San Martino G, Nakov P (2019) Proppy: organizing the news based on their propagandistic content. Signing up enhances your TCE experience with the ability to save items to your personal reading list, and access the interactive map. 24, No. Google Scholar, Bode L, Vraga EK (2015) In related news, that was wrong: the correction of misinformation through related stories functionality in social media. First differences of the multinominal logit modelMorality. 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