(Dis)Information Wars
Over the past decade, social media platforms have emerged as prominent vehicles for displaying dissent. In response, various actors have increasingly spread fake news on these platforms to impair the opposition—the (dis)information war. We analyze a methodology to identify disinformation using network-based characteristics of the news initiators, and use data from Twitter (now X) to assess the effectiveness of this method in limiting the spread of disinformation. We find that it detects at least 85% of verified instances of disinformation without misidentifying any true news, and reduces both account engagement and lifespan of disinformation by at least a factor of two, highlighting the importance of swift discovery of disinformation to interrupt its exponential spread.