Cause and Effect

Misinformation and Biases Infect Social Media, Both Intentionally and Accidentally

Social media are among the primary sources of news in the U.S. and across the world. Yet users are exposed to content of questionable accuracy, including conspiracy theories, clickbait, hyperpartisan content, pseudoscience, and even fabricated “fake news” reports.

It’s not surprising that there’s so much disinformation published: Spam and online fraud are lucrative for criminals, and government and political propaganda yield both partisan and financial benefits. But the fact that low-credibility content spreads so quickly and easily suggests that people and the algorithms behind social media platforms are vulnerable to manipulation.

Explaining the tools developed at the Observatory on Social Media.

Our research has identified three types of bias that make the social media ecosystem vulnerable to both intentional and accidental misinformation. That is why our Observatory on Social Media at Indiana University is building tools to help people become aware of these biases and protect themselves from outside influences designed to exploit them.

Bias in the brain

Cognitive biases originate in the way the brain processes the information that every person encounters every day. The brain can deal with only a finite amount of information, and too many incoming stimuli can cause information overload. That in itself has serious implications for the quality of information on social media. We have found that steep competition for users’ limited attention means that some ideas go viral despite their low quality—even when people prefer to share high-quality content.

To avoid getting overwhelmed, the brain uses a number of tricks. These methods are usually effective, but may also become biases when applied in the wrong contexts.

One cognitive shortcut happens when a person is deciding whether to share a story that appears on their social media feed. People are very affected by the emotional connotations of a headline, even though that’s not a good indicator of an article’s accuracy. Much more important is who wrote the piece.

To counter this bias, and help people pay more attention to the source of a claim before sharing it, we developed Fakey, a mobile news literacy game (free on Android and iOS) simulating a typical social media news feed, with a mix of news articles from mainstream and low-credibility sources. Players get more points for sharing news from reliable sources and flagging suspicious content for fact-checking. In the process, they learn to recognize signals of source credibility, such as hyperpartisan claims and emotionally charged headlines.

Bias in society

Another source of bias comes from society. When people connect directly with their peers, the social biases that guide their selection of friends come to influence the information they see.

In fact, in our research we have found that it is possible to determine the political leanings of a Twitter user by simply looking at the partisan preferences of their friends. Our analysis of the structure of these partisan communication networks found social networks are particularly efficient at disseminating information—accurate or not—when they are closely tied together and disconnected from other parts of society.

The tendency to evaluate information more favorably if it comes from within their own social circles creates “echo chambers” that are ripe for manipulation, either consciously or unintentionally. This helps explain why so many online conversations devolve into “us versus them” confrontations.

To study how the structure of online social networks makes users vulnerable to disinformation, we built Hoaxy, a system that tracks and visualizes the spread of content from low-credibility sources, and how it competes with fact-checking content. Our analysis of the data collected by Hoaxy during the 2016 U.S. presidential elections shows that Twitter accounts that shared misinformation were almost completely cut off from the corrections made by the fact-checkers.

When we drilled down on the misinformation-spreading accounts, we found a very dense core group of accounts retweeting each other almost exclusively—including several bots. The only times that fact-checking organizations were ever quoted or mentioned by the users in the misinformed group were when questioning their legitimacy or claiming the opposite of what they wrote.

Bias in the machine

The third group of biases arises directly from the algorithms used to determine what people see online. Both social media platforms and search engines employ them. These personalization technologies are designed to select only the most engaging and relevant content for each individual user. But in doing so, it may end up reinforcing the cognitive and social biases of users, thus making them even more vulnerable to manipulation.

For instance, the detailed advertising tools built into many social media platforms let disinformation campaigners exploit confirmation bias by tailoring messages to people who are already inclined to believe them.

Also, if a user often clicks on Facebook links from a particular news source, Facebook will tend to show that person more of that site’s content. This so-called “filter bubble” effect may isolate people from diverse perspectives, strengthening confirmation bias.

Our own research shows that social media platforms expose users to a less diverse set of sources than do non-social media sites like Wikipedia. Because this is at the level of a whole platform, not of a single user, we call this the homogeneity bias.

Another important ingredient of social media is information that is trending on the platform, according to what is getting the most clicks. We call this popularity bias, because we have found that an algorithm designed to promote popular content may negatively affect the overall quality of information on the platform. This also feeds into existing cognitive bias, reinforcing what appears to be popular irrespective of its quality.

All these algorithmic biases can be manipulated by social bots, computer programs that interact with humans through social media accounts. Most social bots, like Twitter’s Big Ben, are harmless. However, some conceal their real nature and are used for malicious intents, such as boosting disinformation or falsely creating the appearance of a grassroots movement, also called “astroturfing.” We found evidence of this type of manipulation in the run-up to the 2010 U.S. midterm election.

To study these manipulation strategies, we developed a tool to detect social bots called Botometer. Botometer uses machine learning to detect bot accounts, by inspecting thousands of different features of Twitter accounts, like the times of its posts, how often it tweets, and the accounts it follows and retweets. It is not perfect, but it has revealed that as many as 15 percent of Twitter accounts show signs of being bots.

Using Botometer in conjunction with Hoaxy, we analyzed the core of the misinformation network during the 2016 U.S. presidential campaign. We found many bots exploiting both the cognitive, confirmation and popularity biases of their victims and Twitter’s algorithmic biases.

These bots are able to construct filter bubbles around vulnerable users, feeding them false claims and misinformation. First, they can attract the attention of human users who support a particular candidate by tweeting that candidate’s hashtags or by mentioning and retweeting the person. Then the bots can amplify false claims smearing opponents by retweeting articles from low-credibility sources that match certain keywords. This activity also makes the algorithm highlight for other users false stories that are being shared widely.

Understanding complex vulnerabilities

Even as our research, and others’, shows how individuals, institutions and even entire societies can be manipulated on social media, there are many questions left to answer. It’s especially important to discover how these different biases interact with each other, potentially creating more complex vulnerabilities.

Tools like ours offer internet users more information about disinformation, and therefore some degree of protection from its harms. The solutions will not likely be only technological, though there will probably be some technical aspects to them. But they must take into account the cognitive and social aspects of the problem.

Editor’s note: This article was updated on Jan. 10, 2019, to replace a link to a study that had been retracted. The text of the article is still accurate, and remains unchanged.

Misinformation and Biases Infect Social Media, Both Intentionally and Accidentally by Giovanni Luca Ciampaglia and Filippo Menczer is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

Discussion Questions

1. What are the major causes that make social media vulnerable to misinformation?
2. What are the major effects?
3. Do the examples used in the essay show a causal relationship to the topic? Explain your answers using specific details from the essay.
4. Are the examples used in the essay convincing or persuasive? Explain.
5. Do the authors expose new ideas or knowledge on this topic? Explain why or why not.

Effects of Video Game Addiction

Video game addiction is a serious problem in many parts of the world today and deserves more attention. It is no secret that children and adults in many countries throughout the world, including Japan, China, and the United States, play video games every day. Most players are able to limit their usage in ways that do not interfere with their daily lives, but many others have developed an addiction to playing video games and suffer detrimental effects.

An addiction can be described in several ways, but generally speaking, addictions involve unhealthy attractions to substances or activities that ultimately disrupt the ability of a person to keep up with regular daily responsibilities. Video game addiction typically involves playing games uncontrollably for many hours at a time—some people will play only four hours at a time while others cannot stop for over twenty-four hours.

Regardless of the severity of the addiction, many of the same effects will be experienced by all.

One common effect of video game addiction is isolation and withdrawal from social experiences. Video game players often hide in their homes or in Internet cafés for days at a time—only reemerging for the most pressing tasks and necessities. The effect of this isolation can lead to a breakdown of communication skills and often a loss in socialization. While it is true that many games, especially massive multiplayer online games, involve a very real form of e-based communication and coordination with others, and these virtual interactions often result in real communities that can be healthy for the players, these communities and forms of communication rarely translate to the types of valuable social interaction that humans need to maintain typical social functioning. As a result, the social networking in these online games often gives the users the impression that they are interacting socially, while their true social lives and personal relations may suffer.

Another unfortunate product of the isolation that often accompanies video game addiction is the disruption of the user’s career. While many players manage to enjoy video games and still hold their jobs without problems, others experience challenges at their workplace. Some may only experience warnings or demerits as a result of poorer performance, or others may end up losing their jobs altogether. Playing video games for extended periods of time often involves sleep deprivation, and this tends to carry over to the workplace, reducing production and causing habitual tardiness.

Video game addiction may result in a decline in overall health and hygiene. Players who interact with video games for such significant amounts of time can go an entire day without eating and even longer without basic hygiene tasks, such as using the restroom or bathing. The effects of this behavior pose significant danger to their overall health.

The causes of video game addiction are complex and can vary greatly, but the effects have the potential to be severe. Playing video games can and should be a fun activity for all to enjoy. But just like everything else, the amount of time one spends playing video games needs to be balanced with personal and social responsibilities.

Discussion Questions

1. What are the major causes discussed in this essay?
2. What are the major effects?
3. Do the examples used in the essay show a causal relationship to the topic? Explain your answer using specific details from the essay.
4. Are the examples used in the essay convincing or persuasive? Explain.
5. Does the writer expose new ideas or knowledge on this topic? Why or why not?