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Lucy Chen

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Today, science & R&D social media channels have become just as cluttered as consumer social media channels. For academic researchers, trying to get the word out on your research paper has come to parallel digital and online marketing. It’s as if communicating research main points effectively wasn’t hard enough. Now, even trying to stay afloat on Twitter—much less going viral—is a challenge.This is where data visualizations come in to play. Visualized data, such as charts, infographics, and interactive figures can represent extensive amounts of complicated data more coherently. It's significantly faster to analyze information in graphical format (versus in spreadsheets). Consequently, scientists, government bodies, and businesses are able to spot correlations, patterns, trends, outliers, etc. with greater ease. Data visualization also makes communication possible, effective, and interesting. Getting over the subject-specific learning curve (e.g. jargon) often makes sharing findings to the general public hard--even with other researchers! Using visually impactful representations of data gets the message across quickly, engages new audiences, encourages sharing and visibility, and opens the floor to new research opportunities. Click here to read about How the Scientific Community Reacts to Newly Submitted Preprints.According to Buffer, content with visuals get 94% more total views and visual content is more than 40X more likely to get shared on social media than other types of content. In fact, infographics are liked and shared on social media 3X more than other any other type of content. (MassPlanner) So here are a few common types of data visualizations to help the writer to explain and reader to explore large quantities of data.