We’ve all heard the saying “A picture is worth a thousand words.” Have you ever taken a moment to ask why?
If pictures affect us differently than text, how can we use the power of pictures to enhance our communication? On the other hand, how can we make sure we aren’t being manipulated?
Librarians are experts in managing information, but visual information is viewed, interpreted, accessed, and stored very differently than textual information. Still, though we may need other tools or resources to find and review images, I believe our analytical skills and frameworks are just as relevant to evaluating the value of images as information.
Last year I gave a presentation on the topic “Visual Literacy: Fake News to Fair Use” at two separate library conferences. You can find the full slides from the most recent talk here, if you prefer a visual approach to the topic:
I'm happy to be here at @wilscommunity to talk about "Visual Literacy: From Fake News to Fair Use."
Find my slides here, with lots of links and examples:https://t.co/VCQP4pRMpW
— EBarney (@EBarney) July 24, 2018
Access to Information
Librarians have always cared deeply about access to information, but it’s taken time for the term “literacy” to grow to mean more than just reading text. Now information literacy, media literacy, and visual literacy are all deeply entwined in how we interpret what we find, share and create.
In the transitions from scribes and artists to the printing press, from private collections to public libraries, from personal computers to smartphones, the skills the average person needs to have to find and share information have changed drastically. Lately, the abundance of controversy about what constitutes “fake news” shows how easy access to information doesn’t solve our literacy problems.
Whether we’re discussing the impact of social media on a personal and global level or the value of journalism and free speech, the impact of “Freedom of Information” continues to be a fundamental issue:
“Everyone has the right to freedom of opinion and expression; this right includes freedom to hold opinions without interference and to seek, receive and impart information and ideas through any media and regardless of frontiers.”
– Article 19, Universal Declaration of Human Rights by the United Nations in 1948
The ease of creating and sharing visual information has escalated these changing skills and tools even more rapidly with social media and smartphones. Our understanding of privacy and our social norms for creating, sharing, and publishing images are changing as these tools become more widespread and easy to use.
According to InfoTrends, in 2017 alone people took 1.2 trillion photos – 85 percent on their smartphones.
How does this proliferation of images affect communication?
Emojis & Visual Language
Let’s take emojis as an example. If you use them, you can probably think of ways they may be used to mean something other than the obvious definition – used as humor or innuendo, for instance. Researchers have looked at the way people use specific emoji to create a “secret language” among friends and family:
— Goldsmiths (@GoldsmithsUoL) February 14, 2018
And there are legal implications for image-based messages:
— EBarney (@EBarney) July 25, 2018
What is Visual Literacy?
If I define literacy as a set of skills used to understand, interpret, analyze, research, share, and create information, it can apply to virtually any media.
Yet our visual context can be harder to define or share. We understand what we see by associating it with our personal experiences and larger narratives in our culture. Most people find this helpful for recognizing faces, places, symbols, and brands.
But our context and biases can be easily manipulated with memes and fake news that use stereotypes to build false narratives. If we trust images more quickly and analyze their messages less carefully, it doesn’t help that we’re often missing the original context and interpreting it based on where we find it or who shared it with us.
Here’s a great example of the different interpretations people bring to images, using photojournalism from the Ferguson protests:
- FacingHistory.org: How We Respond to Images
Analyzing Fake News & Memes
Images grab our attention with something we know or recognize. They can convey emotions from fear to humor, from anger to delight. Memes and fake news capitalize on these emotions, often starting with something true and editing or adding something to it to make it more appealing or outrageous, from simple text to complicated photo editing.
Usually we think of fake news as an intentional attempt to confuse or distort truth. But some visual memes may start as jokes that people then read as actual news. In other cases, you could argue images are just advertising but find that creators are using some of the same techniques as fake news by photoshopping products or messages onto people who didn’t originally use or support that content.
Here are three examples I’ve seen in the news or on my own social media feeds in 2018. The “Fauxtography” section of Snopes.com is a great place to fact check for fake images:
- “Crisis Actor” Conspiracy Theory from Mass Shootings
- Kim Jong Un reading Fire and Fury
- LeBron James Protest Shirt
Visual Literacy Analysis
I like this framework for evaluating any resource:
- Identify: What do I know about the context or content?
- Find: Who shared it? Where did they get it? Are they the creator?
- Evaluate: What is the message? Is it accurate? What is the motivation to share it?
- Apply: Can I learn more? Where would I go?
- Acknowledge: How will I respond? If it’s accurate, can I note the author before you share it? If it’s inaccurate, do I want to share that with anyone else?
Fake News Case Study: Russian Twitter Bots, #MeToo & #Oprah2020
Here’s a case study applying that framework with specific tools to debunk a malicious meme designed or attack specific people or distort perceptions of an event.
On January 7, 2018, the 75th annual Golden Globe awards took place while #MeToo stories of abusive Hollywood figures – especially Harvey Weinstein – dominated news headlines. A group of famous actresses in Hollywood responded by wearing black and bringing activists who have been working for fair labor standards or against sexual violence to the awards ceremony.
During the Golden Globes event, Oprah Winfrey was presented a lifetime achievement award and gave a speech that was very well received:
— Golden Globe Awards (@goldenglobes) January 8, 2018
On Twitter, some people responded to the speech with the hashtag #Oprah2020, with varying level of sincerity. The next day, a few news stories asked whether she would want to run for president.
Various versions of this image, adapted into a meme with various titles overlaid on it, began trending via the #Oprah2020 hashtag on social media:
The memes implied, sometimes implicitly and sometimes explicitly, that Oprah Winfrey was aware of the abuses in Hollywood and was willing to actively procure young women for Harvey Weinstein. Many of the accounts sharing the memes also implied this was a partisan political issue.
Personally, my own biases made me doubt Oprah would ever do such a thing. Looking at the image myself and evaluating their body language, I thought the women looked more comfortable with each other than with Harvey Weinstein and the younger woman seemed to be seeking support and perhaps comfort from Oprah Winfrey.
Since the role of Russian bots on Twitter in spreading divisive propaganda in America was been researched extensively in early 2018, I had a quick tool to research the “fake news” implications of this meme.
One site tracked specific Twitter accounts that had been identified as Russian bots and showed what specific messages they were sharing each day. On January 8, 2018, I took this screenshot of the trending hashtags from dashboard.securingdemocracy.org
(as of early January 2019, that tool has been retired and their newer version isn’t available yet)
The top hashtags from these bots that day included:
You can’t always prove quickly that it’s as easy a solution as Russian bots spreading misinformation. But there are other simple tools and strategies you can use if you don’t trust an image.
Reverse Image Search
If you’re looking at a photo online that you suspect may be manipulated or taken out of context, one quick fact check strategy is to do a reverse image search using Google’s Image Search or Tineye.com.
Note: Reverse image searches may not work on mobile devices. On a smartphone? Try this site: https://reverse.photos/.
On my computer, all I had to do was right-click on the image in the Chrome browser and “search by image” to find the original source: a February 2014 article about the young woman, Rita Ora, attending a party in London hosted by the Weinstein Company:
- Would you like fries with that? Rita Ora rubs shoulders with Oprah Winfrey at The Weinstein Company’s post-BAFTA party after grabbing a bite at McDonald’s
A quick search of Rita Ora’s own Twitter feed shows her using other photos from the 2014 event to show her memories didn’t match the Russian Bot meme stories:
— Rita Ora (@RitaOra) January 8, 2018
I learned about this meme from someone else who was already calling out the inaccuracies and sharing the securingdemocracy bot tracker, so I didn’t feel the need to disabuse anyone of the lie directly, but I did bookmark the tool and save some screenshots to share later!
Test Your Skills!
I attended a wonderful presentation at the 2018 CALI conference presented by Carol Watson and Kris Niedringhaus on fake news: Battling Fake News and Developing Digital Literacy Skills within the Legal Profession.
Here are a few of the websites and apps the speakers recommended to help verify the accuracy of news or to test your own skills in evaluating fake headlines.
- FotoForensics: check photos for signs of editing
- Factitious: a quiz game to test your ability to spot fake & real news
- Get Bad News: see how fake news spreads
- BBC iReporter: create click-bait headlines
- B. S. Detector: a browser add-on to get alerts for unreliable news, by type
I also enjoyed the range of articles recommended at their CALIcon18 presentation. I’ve shared my full notes on this Twitter thread, since I haven’t found their slides online.
- How to Spot Fake News (FactCheck.org, Eugene Kiely & Lori Robertson, 11/18/2016)
- A lesson in fake news from the info-wars of ancient Rome (Financial Times, Izabella Kaminska, 1/17/2017)
- The Myth of the War of the Worlds Panic (Slate.com, Jefferson Pooley & Michael Socolow, 10/28/2013)
- The Macedonian Teens Who Mastered Fake News (Wired, Samanth Subramanian, 2/15/2017)
- Lies spread faster than the truth (Science, Barbara R. Jasny, 3/9/2018)
If we’re more easily influenced to believe images than text, how much more are we going to be manipulated by videos? If you haven’t heard of software that makes these “deep fakes” easy to do, you may want to read this article:
- The Era of Fake Video Begins (The Atlantic, Franklin Foer, 5/2018)
Here’s an example designed to help you see how the skills and questions I’ve described above can be applied to videos that may have been manipulated using new software:
— BuzzFeed News (@BuzzFeedNews) April 17, 2018