A rumor is information that may or may not be true. It can be a story about anything: a celebrity visiting town, a famous person being fired from their job, or that the school is closing early due to a snowstorm. Some rumors can be confirmed, but many cannot. Rumors are often based on hearsay, which means that the information was passed from person to person without evidence. A person who loves spreading rumors is known as a rumormonger.
Social scientists have studied rumors for years. The modern scholarly definition of a rumor is based on the pioneering work of Louis William Stern in 1902. Stern experimented with a chain of subjects who passed a story from mouth to ear without repeating or explaining it, and found that the story was shortened and altered every time it was shared.
While a rumor is unconfirmed, it is perceived to be important or significant. It is often related to current events or topics of interest, but it can also be a partisan political ploy. Rumors can be of a serious nature or they can be humorous.
There are several factors that influence a rumor’s accuracy, including the level of anxiety (situational and personality), the ability to verify the rumor, the desire for relationship- and self-enhancement, the availability of a source for the rumor, the degree of ambiguity in the rumor, and the importance of the rumor. Accuracy is increased when the rumor is transmitted via communication channels that have existed for some time, when it is checked against other sources, when there is discussion about the rumor, and when it is conveyed by people who are motivated to ferret out the truth.
Twitter is a popular medium for sharing rumors. However, there are a lot of rumors being spread on Twitter that are not true. These rumors are often false, fabricated, or exaggerated and they can affect the way we perceive the world around us.
Researchers are working on different ways to categorize rumors and determine which ones are true or false. One approach uses crowd classification based on personality traits. For example, those who are more radical tend to believe what they hear and they tend to share rumors more quickly. Those who are steady and calm, on the other hand, may spend more time considering the credibility of the rumor and will only pass it along if they think it is accurate.
Another method uses a machine learning algorithm to analyze the patterns in tweets. It looks for evidence of the rumor in the form of a URL, a quote from an accessible source, or an explanation of why the rumor is true. It then calculates the average z-score of the tweet, which is the number of standard deviations it is above or below the global average. The rumors that are most likely to be true have the highest z-score. The rumors that are most likely to false or fabricated have the lowest z-score.