Social media is the best friend disinformation ever had, and the cure is far from obvious.
Anya Schiffrin is an adjunct faculty member at the School of International and Public Affairs at Columbia University. She worked in Hanoi from 1997 to 1999 as the bureau chief of Dow Jones Newswires.
Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics By Yochai Benkler, Robert Faris, & Hal Roberts
Oxford University Press
A Harvard law professor who is a well-known theorist of the digital age, Benkler and colleagues have produced an authoritative tome that includes multiple taxonomies and literature reviews as well as visualizations of the flow of disinformation.
clickbait fabricators
white supremacist and alt-right trolls
a history of the scholarship on propaganda, reminding the reader that much of the discussion began in the 1930s.
Benkler’s optimistic 2007 book, The Wealth of Networks, predicted that the Internet would bring people together and transform the way information is created and spread. Today, Benkler is far less sanguine and has become one of the foremost researchers of disinformation networks.
Fox News, Breitbart, The Daily Caller, InfoWars, and Zero Hedge
As a result, mainstream journalists repeat and amplify the falsehoods even as they debunk them.
There is no clear line, they argue, between Russian propaganda, Breitbart lies, and the Trump victory. They add that Fox News is probably more influential than Facebook.
after George Soros gave a speech in January 2018 calling for regulation of the social media platforms, Facebook hired a Republican opposition research firm to shovel dirt at George Soros.
The European Union has not yet tried to regulate disinformation (although they do have codes of practice for the platforms), instead focusing on taxation, competition regulation, and protection of privacy. But Germany has strengthened its regulations regarding online hate speech, including the liability of the social media platforms.
disclosure of the sources of online political advertising.It’s a bit toothless because, just as with offshore bank accounts, it may be possible to register which U.S. entity is paying for online political advertising, but it’s impossible to know whether that entity is getting its funds from overseas. Even the Honest Ads bill was too much for Facebook to take.
Others have likened habitual Facebook use to a mental disorder, comparing it to drug addiction and even publishing magnetic-resonance images of what Facebook addiction “looks like in the brain.”
For abstainers, breaking up with Facebook freed up about an hour a day, on average, and more than twice that for the heaviest users.
research led by Ethan Kross, a professor of psychology at the University of Michigan, has found that high levels of passive browsing on social media predict lowered moods, compared to more active engagement.
Scholars want peers to find—and cite—their research, and these days that increasingly happens on social media. The old adage ‘publish or perish’ could soon go digital as ‘clicks or canned.’
Several platforms have emerged over the past decade, offering researchers the chance to share their work and connect with other scholars. But some of those services have a bad rap from academics who say commercial sites lack the integrity of institutional repositories run by traditional universities. (Among the most widely-villified are ResearchGate and Academia.edu, which is evident by griping on social media and elsewhere.)
a 2015 paper comparing services and tools offered by various academic social networks, says researchers must weigh the benefits and drawbacks of each. “They can be great tools to advance your research, especially social research,” she says. “But just like with Facebook or any other social network, we need to be aware of potential issues we might have with copyright or privacy.”
Academia.edu is the largest of the academic social networks.
Created as a reference-management tool to help users organize their research, Mendeley also includes a number of social-networking features.
Scholabrate. The service claims to provide a more Facebook-esque, visual experience for academics seeking to network with others in their field.
Similar to Mendeley, Zotero functions primarily as a research tool, allowing users to collect, save, cite and share materials from a wide range of sources. The site also maintains a significant community of academics who can connect through groups and forums, or through their search engine.
The overuse of technology has overtaken drugs, sex and bullying as the biggest parental worry, according to the annual Brigham Young and Deseret News American Family Survey.
The American Academy of Pediatrics supports this idea of joint media engagement, basically engaging alongside your kids, as you suggest, whether with games, videos or social media. But isn’t there such a thing as too much screen time?
When people talk about addiction, I think it’s weird we want to blame the digital media because you can form unhealthy relationships with lots of things — food, sex, work, money.
We’re using screens as a babysitter.
There’s an interesting study that recently came out that looked at how parents and young children were interacting around devices. It showed that this joint media engagement is not happening.
I feel like part of the problem is that parents are getting essentially abstinence-only education, like in sex education. The research on that says, if all you hear is, “Just say no,” it has no positive effects.
Nobody actually thinks we’re going to have a world without [tech]. They’re aiming for that healthy relationship. A healthy relationship is you being able to have the autonomy to make good decisions.
THERE’S A MEME on Instagram, circulated by a group called “Born Liberal.” “Born Liberal” was a creation of the Internet Research Agency, the Russian propaganda wing
Conversations around the IRA’s operations traditionally have focused on Facebook and Twitter, but like any hip millennial, the IRA was actually most obsessive about Instagram.
the IRA deployed 3,841 accounts, including several personas that “regularly played hashtag games.” That approach paid off; 1.4 million people engaged with the tweets, leading to nearly 73 million engagements. Most of this work was focused on news, while on Facebook and Instagram, the Russians prioritized “deeper relationships,” according to the researchers. On Facebook, the IRA notched a total of 3.3 million page followers, who engaged with their politically divisive content 76.5 million times. Russia’s most popular pages targeted the right wing and the black community. The trolls also knew their audiences; they deployed Pepe memes at pages intended for right-leaning millennials, but kept them away from posts directed at older conservative Facebook users. Not every attempt was a hit; while 33 of the 81 IRA Facebook pages had over 1,000 followers, dozens had none at all.
The report also points out new links between the IRA’s pages and Wikileaks, which helped disseminate hacked emails from Clinton campaign manager John Podesta
“While many people think of memes as “cat pictures with words,” the Defense Department and DARPA have studied them for years as a powerful tool of cultural influence, capable of reinforcing or even changing values and behavior.
“over the past five years, disinformation has evolved from a nuisance into high-stakes information war.” And yet, rather than fighting back effectively, Americans are battling each other over what to do about it.
A year after the Meme Warfare Center proposal was published, DARPA, the Pentagon agency that develops new military technology, commissioned a four-year study of memetics. The research was led by Dr. Robert Finkelstein, founder of the Robotic Technology Institute, and an academic with a background in physics and cybernetics.
Finkelstein’s study of “Military Memetics” centered on a basic problem in the field, determining “whether memetics can be established as a science with the ability to explain and predict phenomena.” It still had to be proved, in other words, that memes were actual components of reality and not just a nifty concept with great marketing.
Summary This short paper lays out an attempt to measure how much activity from Russian state-operated accounts released in the dataset made available by Twitter in October 2018 was targeted at the United Kingdom. Finding UK-related Tweets is not an easy task. By applying a combination of geographic inference, keyword analysis and classification by algorithm, we identified UK-related Tweets sent by these accounts and subjected them to further qualitative and quantitative analytic techniques.
We find:
There were three phases in Russian influence operations : under-the-radar account building, minor Brexit vote visibility, and larger-scale visibility during the London terror attacks.
Russian influence operations linked to the UK were most visible when discussing Islam . Tweets discussing Islam over the period of terror attacks between March and June 2017 were retweeted 25 times more often than their other messages.
The most widely-followed and visible troll account, @TEN_GOP, shared 109 Tweets related to the UK. Of these, 60 percent were related to Islam .
The topology of tweet activity underlines the vulnerability of social media users to disinformation in the wake of a tragedy or outrage.
Focus on the UK was a minor part of wider influence operations in this data . Of the nine million Tweets released by Twitter, 3.1 million were in English (34 percent). Of these 3.1 million, we estimate 83 thousand were in some way linked to the UK (2.7%). Those Tweets were shared 222 thousand times. It is plausible we are therefore seeing how the UK was caught up in Russian operations against the US .
Influence operations captured in this data show attempts to falsely amplify other news sources and to take part in conversations around Islam , and rarely show attempts to spread ‘fake news’ or influence at an electoral level.
On 17 October 2018, Twitter released data about 9 million tweets from 3,841 blocked accounts affiliated with the Internet Research Agency (IRA) – a Russian organisation founded in 2013 and based in St Petersburg, accused of using social media platforms to push pro-Kremlin propaganda and influence nation states beyond their borders, as well as being tasked with spreading pro-Kremlin messaging in Russia. It is one of the first major datasets linked to state-operated accounts engaging in influence operations released by a social media platform.
Conclusion
This report outlines the ways in which accounts linked to the Russian Internet ResearchAgency (IRA) carried out influence operations on social media and the ways their operationsintersected with the UK.The UK plays a reasonably small part in the wider context of this data. We see two possibleexplanations: either influence operations were primarily targeted at the US and British Twitterusers were impacted as collate, or this dataset is limited to US-focused operations whereevents in the UK were highlighted in an attempt to impact US public, rather than a concertedeffort against the UK. It is plausible that such efforts al so existed but are not reflected inthis dataset.Nevertheless, the data offers a highly useful window into how Russian influence operationsare carried out, as well as highlighting the moments when we might be most vulnerable tothem.Between 2011 and 2016, these state-operated accounts were camouflaged. Through manualand automated methods, they were able to quietly build up the trappings of an active andwell-followed Twitter account before eventually pivoting into attempts to influence the widerTwitter ecosystem. Their methods included engaging in unrelated and innocuous topics ofconversation, often through automated methods, and through sharing and engaging withother, more mainstream sources of news.Although this data shows levels of electoral and party-political influence operations to berelatively low, the day of the Brexit referendum results showed how messaging originatingfrom Russian state-controlled accounts might come to be visible – on June 24th 2016, we believe UK Twitter users discussing the Brexit Vote would have encountered messages originating from these accounts.As early as 2014, however, influence operations began taking part in conversations aroundIslam, and these accounts came to the fore during the three months of terror attacks thattook place between March and June 2017. In the immediate wake of these attacks, messagesrelated to Islam and circulated by Russian state-operated Twitter accounts were widelyshared, and would likely have been visible in the UK.The dataset released by Twitter begins to answer some questions about attempts by a foreignstate to interfere in British affairs online. It is notable that overt political or electoralinterference is poorly represented in this dataset: rather, we see attempts at stirring societaldivision, particularly around Islam in the UK, as the messages that resonated the most overthe period.What is perhaps most interesting about this moment is its portrayal of when we as socialmedia users are most vulnerable to the kinds of messages circulated by those looking toinfluence us. In the immediate aftermath of terror attacks, the data suggests, social mediausers were more receptive to this kind of messaging than at any other time.
It is clear that hostile states have identified the growth of online news and social media as aweak spot, and that significant effort has gone into attempting to exploit new media toinfluence its users. Understanding the ways in which these platforms have been used tospread division is an important first step to fighting it.Nevertheless, it is clear that this dataset provides just one window into the ways in whichforeign states have attempted to use online platforms as part of wider information warfare
and influence campaigns. We hope that other platforms will follow Twitter’s lead and release
similar datasets and encourage their users to proactively tackle those who would abuse theirplatforms.
Digital Fluency: Preparing Learners for 21st Century Digital Citizenship Eighty-five percent of the jobs available in 2030 do not yet exist. How does higher education prepare our learners for careers that don’t yet exist? One opportunity is to provide our students with opportunities to grow their skills in creative problem solving, critical thinking, resiliency, novel thinking, social intelligence, and excellent communication skills. Instructional designers and faculty can leverage the framework of digital fluency to create opportunities for learners to practice and hone the skills that will prepare them to be 21st-century digital citizens. In this session, join a discussion about several fluencies that comprise the overarching framework for digital fluency and help to define some of your own.
Dr. Jennifer Sparrow, Senior Director for Teaching and Learning with Technology and Affiliate Assistant Professor of Learning, Design, and Technology at Penn State. The webinar will take place on Friday, November 9th at 11am EST/4pm UTC (login details below)
how DF is different from DLiteracy? enable students define how new knowledge can be created through technology. Not only read and write, but create poems, stories, if analogous w learning a language. slide 4 in https://www.slideshare.net/aidemoreto/vr-library
communication fluency. be able to choose the correct media. curiosity/failure fluency; creation fluency (makerspace: create without soldering, programming, 3Dprinting. PLA filament-corn-based plastic; Makers-in-residence)
immersive fluency: video 360, VR and AR. enable student to create new knowledge through environments beyond reality. Immersive Experiences Lab (IMEX). Design: physical vs virtual spaces.
Data fluency: b.book. how to create my own textbook
rubrics and sample projects to assess digital fluency.
What is Instructional Design 2.0 or 3.0? deep knowledge and understanding of faculty development. second, once faculty understands the new technology, how does this translate into rework of curriculum? third, the research piece; how to improve to be ready for the next cycle. a partnership between ID and faculty.
United States digital literacy frameworks tend to focus on educational policy details and personal empowerment, the latter encouraging learners to become more effective students, better creators, smarter information consumers, and more influential members of their community.
National policies are vitally important in European digital literacy work, unsurprising for a continent well populated with nation-states and struggling to redefine itself, while still trying to grow economies in the wake of the 2008 financial crisis and subsequent financial pressures
African digital literacy is more business-oriented.
Middle Eastern nations offer yet another variation, with a strong focus on media literacy. As with other regions, this can be a response to countries with strong state influence or control over local media. It can also represent a drive to produce more locally-sourced content, as opposed to consuming material from abroad, which may elicit criticism of neocolonialism or religious challenges.
p. 14 Digital literacy for Humanities: What does it mean to be digitally literate in history, literature, or philosophy? Creativity in these disciplines often involves textuality, given the large role writing plays in them, as, for example, in the Folger Shakespeare Library’s instructor’s guide. In the digital realm, this can include web-based writing through social media, along with the creation of multimedia projects through posters, presentations, and video. Information literacy remains a key part of digital literacy in the humanities. The digital humanities movement has not seen much connection with digital literacy, unfortunately, but their alignment seems likely, given the turn toward using digital technologies to explore humanities questions. That development could then foster a spread of other technologies and approaches to the rest of the humanities, including mapping, data visualization, text mining, web-based digital archives, and “distant reading” (working with very large bodies of texts). The digital humanities’ emphasis on making projects may also increase
Digital Literacy for Business: Digital literacy in this world is focused on manipulation of data, from spreadsheets to more advanced modeling software, leading up to degrees in management information systems. Management classes unsurprisingly focus on how to organize people working on and with digital tools.
Digital Literacy for Computer Science: Naturally, coding appears as a central competency within this discipline. Other aspects of the digital world feature prominently, including hardware and network architecture. Some courses housed within the computer science discipline offer a deeper examination of the impact of computing on society and politics, along with how to use digital tools. Media production plays a minor role here, beyond publications (posters, videos), as many institutions assign multimedia to other departments. Looking forward to a future when automation has become both more widespread and powerful, developing artificial intelligence projects will potentially play a role in computer science literacy.
In traditional instruction, students’ first contact with new ideas happens in class, usually through direct instruction from the professor; after exposure to the basics, students are turned out of the classroom to tackle the most difficult tasks in learning — those that involve application, analysis, synthesis, and creativity — in their individual spaces. Flipped learning reverses this, by moving first contact with new concepts to the individual space and using the newly-expanded time in class for students to pursue difficult, higher-level tasks together, with the instructor as a guide.
Let’s take a look at some of the myths about flipped learning and try to find the facts.
Myth: Flipped learning is predicated on recording videos for students to watch before class.
Fact: Flipped learning does not require video. Although many real-life implementations of flipped learning use video, there’s nothing that says video must be used. In fact, one of the earliest instances of flipped learning — Eric Mazur’s peer instruction concept, used in Harvard physics classes — uses no video but rather an online text outfitted with social annotation software. And one of the most successful public instances of flipped learning, an edX course on numerical methods designed by Lorena Barba of George Washington University, uses precisely one video. Video is simply not necessary for flipped learning, and many alternatives to video can lead to effective flipped learning environments [http://rtalbert.org/flipped-learning-without-video/].
Fact: Flipped learning optimizes face-to-face teaching. Flipped learning may (but does not always) replace lectures in class, but this is not to say that it replaces teaching. Teaching and “telling” are not the same thing.
Myth: Flipped learning has no evidence to back up its effectiveness.
Fact: Flipped learning research is growing at an exponential pace and has been since at least 2014. That research — 131 peer-reviewed articles in the first half of 2017 alone — includes results from primary, secondary, and postsecondary education in nearly every discipline, most showing significant improvements in student learning, motivation, and critical thinking skills.
Myth: Flipped learning is a fad.
Fact: Flipped learning has been with us in the form defined here for nearly 20 years.
Myth: People have been doing flipped learning for centuries.
Fact: Flipped learning is not just a rebranding of old techniques. The basic concept of students doing individually active work to encounter new ideas that are then built upon in class is almost as old as the university itself. So flipped learning is, in a real sense, a modern means of returning higher education to its roots. Even so, flipped learning is different from these time-honored techniques.
Myth: Students and professors prefer lecture over flipped learning.
Fact: Students and professors embrace flipped learning once they understand the benefits. It’s true that professors often enjoy their lectures, and students often enjoy being lectured to. But the question is not who “enjoys” what, but rather what helps students learn the best.They know what the research says about the effectiveness of active learning
Assertion: Flipped learning provides a platform for implementing active learning in a way that works powerfully for students.
The Exposure Approach: we don’t provide a way for participants to determine if they learned anything new or now have the confidence or competence to apply what they learned.
The Exemplar Approach: from ‘show and tell’ for adults to show, tell, do and learn.
The Tutorial Approach: Getting a group that can meet at the same time and place can be challenging. That is why many faculty report a preference for self-paced professional development.build in simple self-assessment checks. We can add prompts that invite people to engage in some sort of follow up activity with a colleague. We can also add an elective option for faculty in a tutorial to actually create or do something with what they learned and then submit it for direct or narrative feedback.
The Course Approach: a non-credit format, these have the benefits of a more structured and lengthy learning experience, even if they are just three to five-week short courses that meet online or in-person once every week or two.involve badges, portfolios, peer assessment, self-assessment, or one-on-one feedback from a facilitator
The Academy Approach: like the course approach, is one that tends to be a deeper and more extended experience. People might gather in a cohort over a year or longer.Assessment through coaching and mentoring, the use of portfolios, peer feedback and much more can be easily incorporated to add a rich assessment element to such longer-term professional development programs.
The Mentoring Approach: The mentors often don’t set specific learning goals with the mentee. Instead, it is often a set of structured meetings, but also someone to whom mentees can turn with questions and tips along the way.
The Coaching Approach: A mentor tends to be a broader type of relationship with a person.A coaching relationship tends to be more focused upon specific goals, tasks or outcomes.
The Peer Approach:This can be done on a 1:1 basis or in small groups, where those who are teaching the same courses are able to compare notes on curricula and teaching models. They might give each other feedback on how to teach certain concepts, how to write syllabi, how to handle certain teaching and learning challenges, and much more. Faculty might sit in on each other’s courses, observe, and give feedback afterward.
The Self-Directed Approach:a self-assessment strategy such as setting goals and creating simple checklists and rubrics to monitor our progress. Or, we invite feedback from colleagues, often in a narrative and/or informal format. We might also create a portfolio of our work, or engage in some sort of learning journal that documents our thoughts, experiments, experiences, and learning along the way.
In 2014, administrators at Central Piedmont Community College (CPCC) in Charlotte, North Carolina, began talks with members of the North Carolina State Board of Community Colleges and North Carolina Community College System (NCCCS) leadership about starting a CBE program.
Building on an existing project at CPCC for identifying the elements of a digital learning environment (DLE), which was itself influenced by the EDUCAUSE publication The Next Generation Digital Learning Environment: A Report on Research,1 the committee reached consensus on a DLE concept and a shared lexicon: the “Digital Learning Environment Operational Definitions,
College students’ perceptions of pleasure in learning – Designing gameful gamification in education
investigate behavioral and psychological metrics that could affect learner perceptions of technology
today’s learners spend extensive time and effort posting and commenting in social media and playing video games
Creating pleasurable learning experiences for learners can improve learner engagement.
uses game-design elements in non-gaming environments with the purpose of motivating users to behave in a certain direction (Deterding et al., 2011)
How can we facilitate the gamefulness of gamification?
Most gamified activities include three basic parts: “goal-focused activity, reward mechanisms, and progress tracking” (Glover, 2013, p. 2000).
gamification works similarly to the instructional methods in education – clear learning and teaching objectives, meaningful learning activities, and assessment methods that are aligned with the objectives
the design of seven game elements:
Storytelling: It provides the rules of the gamified activities. A good gamified activity should have a clear and simple storyboard to direct learners to achieve the goals. This game-design element works like the guidelines and directions of an instructional activity in class.
Levels: A gamified activity usually consists of different levels for learners to advance through. At each level, learners will face different challenges. These levels and challenges can be viewed as the specific learning objectives/competencies for learners to accomplish.
Points: Points pertain to the progress-tracking element because learners can gain points when they complete the quests.
Leaderboard: This element provides a reward mechanism that shows which learners are leading in the gamified activities. This element is very controversial when gamification is used in educational contexts because some empirical evidence shows that a leaderboard is effective only for users who are aggressive and hardcore players (Hamari, Koivisto, & Sarsa, 2014).
Badges: These serve as milestones to resemble the rewards that learners have achieved when they complete certain quests. This element works as the extrinsic motivation for learners (Kapp, 2012).
Feedback: A well-designed gamification interface should provide learners with timely feedback in order to help them to stay on the right track.
Progress: A progress-tracking bar should appear in the learner profile to remind learners of how many quests remain and how many quests they have completed.
Dominguez et al. (2013) suggested that gamification fosters high-order thinking, such as problem-solving skills, rather than factual knowledge. Critical thinking, which is commonly assessed in social science majors, is also a form of higher-order thinking.
Davis (1989) developed technology acceptance model (TAM) to help people understand how users perceive technologies. Pleasure, arousal, and dominance (PAD) emotional-state model that developed by Mehrabian (1995) is one of the fundamental design frameworks for scale development in understanding user perceptions of user-system interactions.
Van der Heijdedn (2004) asserted that pleasurable experiences encouraged users to use the system for a longer period of time Self-determination theory (Deci & Ryan, 1985) has been integrated into the design of gamification and addressed the balance between learners’ extrinsic and intrinsic motivation.
Ryan and Deci (2000) concluded that extrinsic rewards might suppress learners’ intrinsic motivation. Exploiting the playfulness and gamefulness in gamification, therefore, becomes extremely important, as it would employ the most effective approaches to engage learners.
Sweetser and Wyeth (2005) developed GameFlow as an evaluation model to measure player enjoyment in games
Fu, Su, and Yu (2009) adapted this scale to EGameFlow in order to measure college students’ enjoyment of e-learning games. EGameFlow is a multidimensional scale that consists of self-evaluated emotions.
Eppmann, Bekk, and Klein (2018) developed gameful experience scale (GAMEX) to measure gameful experiences for gamification contexts. one of the limitations of GAMEX to be used in education is that its effects on learning outcome has not been studied
the Big Five Model, which has been proposed as trait theory by McCrae & Costa (1989) and is widely accepted in the field, to measure the linkages between the game mechanics in gamification and the influences of different personality traits.
Storytelling in the subscale of Preferences for Instruction emphasizes the rules of the gamified learning environments, such as the syllabus of the course, the rubrics for the assignments, and the directions for tasks. Storytelling in the subscale of Preferences for Instructors’ Teaching Style focuses on the ways in which instructors present the content. For example, instructors could use multimedia resources to present their instructional materials. Storytelling in the subscale of Preferences for Learning Effectiveness emphasizes scaffolding materials for the learners, such as providing background information for newly introduced topics.
The effective use of badges would include three main elements: signifier, completion logic, and rewards (Hamari & Eranti, 2011). A useful badge needs clear goal-setting and prompt feedback. Therefore, badges correlate closely with the design of storytelling (rules) and feedback, which are the key game design elements in the subscale of Preferences for Instruction.
Students can use Google to search on their laptops or tablets in class when instructors introduce new concepts. By reading the reviews and viewing the numbers of “thumbs-up” (agreements by other users), students are able to select the best answers. Today’s learners also “tweet” on social media to share educational videos and news with their classmates and instructors. Well-designed gamified learning environments could increase pleasure in learning by allowing students to use familiar computing experiences in learning environments.
Falsehoods are spread due to biases in the brain, society, and computer algorithms (Ciampaglia & Menczer, 2018). A combined problem is “information overload and limited attention contribute to a degradation of the market’s discriminative power” (Qiu, Oliveira, Shirazi, Flammini, & Menczer, 2017). Falsehoods spread quickly in the US through social media because this has become Americans’ preferred way to read the news (59%) in the 21st century (Mitchell, Gottfried, Barthel, & Sheer, 2016). While a mature critical reader may recognize a hoax disguised as news, there are those who share it intentionally. A 2016 US poll revealed that 23% of American adults had shared misinformation unwittingly or on purpose; this poll reported high to moderate confidence in one’s ability to identify fake news with only 15% not very confident (Barthel, Mitchell, & Holcomb, 2016).
Hoaxy® takes it one step further and shows you who is spreading or debunking a hoax or disinformation on Twitter.
