The key finding from the team’s analysis was that, on average, the fake news headlines were more negative than the mainstream ones in each period. Of course, that just shows “that fake news headlines contain more negative words in the title than real news,” research scientist Haewoon Kwak told Engadget.
Inferring meaning from this requires some guesswork, and there are two possible explanations, according to Kwak. Either fake news writers are intentionally doing this for “clickbait” purposes, or they “naturally use more negative words” because of the topics they’re writing about. An in-depth qualitative study might show which of the explanations is valid, but given the fake news writers were generally trying to make money from clicks, the former seems likely to be a driving factor.
Looking across the three periods, something else becomes clear: The average sentiment of real news became slightly more negative (from -0.14 to -0.2) while fake news became more positive (from -0.4 to -0.23). “This contradicts with our expectation that fake news became more aggressive over time,” said Kwak. Look at the stories themselves, though, and you can see the problem with the sentiment analysis. The fake news headlines in the pre-election period are atypical. Unlike those of traditional news, these headlines are complex, long and often switch viewpoint.
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