Sentiment analysis can be used to gauge public opinion on everything from political candidates to new product launches, but its accuracy is heavily influenced by the nuances of human language, including sarcasm and slang.
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Computational social science methods can analyze vast datasets of social media posts to track the spread of misinformation in real time, allowing for faster interventions.
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Neural networks can be surprisingly good at tasks they weren't explicitly trained for, exhibiting a phenomenon called "emergent behavior." This means they can sometimes solve problems related to their training, but not directly part of it.
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The amount of data generated globally each day is so vast that it would take you longer than a lifetime to watch all the videos uploaded to YouTube in a single day.
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