One question some people have about the openness of the web, including social networks, is about navigating information that proves to be false. The survey probed Twitter users about that experience as well. The findings suggest that there is some self-correcting element to Twitter and to the web generally, born in part out of the multiplicity of information sources and also out of some degree of skepticism by Twitter users about the information they encounter.
In all, 64% of Twitter news users said they had encountered something on Twitter they later discovered wasn’t true. Interestingly, relatively few people said they had ever passed those tweets along. Just 16% of Twitter news users said they had retweeted or posted a tweet they later discovered to be false.
There were various ways Twitter users said they discovered that something they saw was wrong, which gets to the multiplicity of the correcting nature of the platform. Sixty-two percent of those who encountered a false tweet said they discovered it from another source outside Twitter. Nearly as many, 59%, said they saw a tweet alerting them to the problem. Four out of 10, 43%, said they were alerted to the problem by a later tweet from the same source correcting their mistake. A much smaller number, 21%, said they heard about it from someone later through word of mouth. In other words, the web as a system and Twitter itself has some self correction to it.
| Where corrective information was found | Percent |
|---|---|
| Another source, not on Twitter, debunking the report | 62% |
| Through a tweet from a different person or news source debunking the report | 59% |
| Through a later tweet from the same source correcting the mistake | 43% |
| Word of mouth | 21% |
| Other | 6% |
| I can’t remember |
Data Source: Question: Have you ever encountered a tweet that you later found out wasn't true? / Thinking about the last time you found out a tweet you had seen was inaccurate, how did you discover it wasn't true? Please select all that apply. (Base: Twitter Users N=3713)
American Press Institute, DB5 and Twitter
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