The conversations that trend on internet platforms shape our world in consequential ways, from who we vote for, to what news we read, to how we respond to a pandemic.
But frequently, these conversations don’t trend organically — they’re the result of influence campaigns intended to misinform, radicalize, or polarize. Rather than public opinion influencing the trends, social media trends influence public opinion.
So today, Mozilla Fellow Emmi Bevensee is co-launching the Social Media Analysis Toolkit (SMAT) — a free, intuitive, and open-source tool for scrutinizing online conversations. The tool is available in English and Spanish.
SMAT uses intuitive UX and crisp data visualizations to unpack what’s being said on Twitter, Reddit, 4chan, and 8chan (Insight into other platforms, like Telegram, Parler, and Gab will be available soon.) SMAT’s database structure means that results load instantly; on similar tools, loading can be slow due to integration with various APIs. All results can be exported via CSV. The SMAT team is also developing publicly-accessible tools for monitoring the U.S. elections, such as interactive network graphs of politicians that help to map things like spheres of influence and partisanship.
Users can study everything from what’s trending during a certain period of time, to who is driving the conversation, to what links are being shared the most, and beyond. For example, a researcher looking into COVID conspiracies can determine when the conspiracy began, who is leading the conversation, and which news stories, blog posts, and other links are appearing most frequently in the online conversation.
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