Contrary to the common notion that big data is exclusive to the science domains, Taboada is leveraging big data in an unexpected one: linguistics. Researchers across all disciplines are starting to understand how applying big data approaches can advance their research. Simon Fraser University empowers these researchers to unlock the potential of big data by offering powerful infrastructure, hands-on training, and expertise to deliver new research breakthroughs and innovations.
Traditionally, Natural Language Processing is great at classifying text, assigning it to pre-defined categories and semantic analysis, like text summarization. But Taboada is taking an innovative big data approach with Natural Language Processing, creating breakthroughs in identifying fake news and toxic comments — solutions desperately needed now more than ever. By using machine learning and deep learning neural networks, she can create programs that not only understand and classify words, but also exploit contextual information that helps machines better understand the nuances of language. Taboada and SFU postdoctoral fellow Fatemeh Torabi Asr believe that there is a language of fake news – a language for wrapping false information around facts. They found that fake news is shared more often than real news, making their research vital in stemming the spread of misinformation. Outside of social media, this approach is often used in spam detection, product review analysis, coding medical patient records and a variety of other problems dealing with data in online platforms.
“Most of the big data revolution in social media analysis has examined words in isolation, a ‘bag-of-words’ approach,” Taboada explains. “We believe it is possible to investigate big data—and social media data in general—by exploiting contextual information. This is important when detecting whether a comment is sarcastic—and therefore toxic—or harmless.”
With the alarming rise of fake news and online harassment endemic in comment sections, Taboada and her team are hard at work creating a fast and reliable way to identify bias and misinformation in news articles, potentially changing the landscape of how news is shared and engaged with online. If news shared on social media can be checked for accuracy, and toxic comments are automatically filtered to encourage thoughtful discussion, the perception of social media—and the way we engage with news over it—just might fundamentally change.
No one knows what the future of social media holds, as the public has started to understand its pitfalls and shortcomings. One thing that is desperately needed—with companies like Facebook and Google expending immense resources and money towards solving—is the problem of fake news and online harassment. Taboada is not just building solutions these companies urgently want — she is creating hope that one day, we will have a platform that people can share, engage, critique and foster conversation about the world around us in an environment that encourages respect for the human beings on the other side of the screen. All thanks to harnessing the power of big data.
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