Summary In today's episode, I investigate the dead internet theory and why bots increasingly populate social media feeds. Here's what this means for you. You gain the tools to recognize and navigate a digital landscape of artificial interactions. You'll also learn these concepts: why algorithms incentivize performative bot behavior, how to reclaim your social feed…
Summary In today's episode, I sit down with Julia Freeland Fisher to explore how social capital and AI are reshaping the labor market for today's students and graduates. Here's what this means for you. You gain a framework for understanding why networks, exposure, and credibility still matter even as generative AI is eroding traditional entry-level…
In today’s episode, get ready to dive into the future of social listening and discover why the methods you’re using now will soon be obsolete. You’ll learn how large language models are changing the game, why social media companies are guarding their data more closely than ever, and the steps you need to take to…
In today’s episode, Mike questions why social media can sometimes feel like a “dumpster fire.” You’ll explore the role of machine learning algorithms in shaping your social media experience, focusing on engagement metrics like likes, comments, and shares. Discover how your interactions with content dictate what you see more of on your feeds. Tune in…
Summary In today's episode, I address whether Twitter remains a reliable platform and where to turn if it isn't. Here's what this means for you. You gain an honest assessment of Twitter's current vulnerabilities and practical alternatives for professional networking and credible sourcing. You'll also learn these concepts: why Twitter's open-sourced recommendation engine creates security…
In this video, Christopher Penn discusses the new trend of public social networks and SaaS based services offering more paid services to generate revenue. He questions the companies’ motivation for moving security behind a paywall and notes that it may compromise data security for non-paying customers. The video suggests exploring alternative social media platforms like…
Christopher Penn discusses the importance of testing assumptions in social media algorithms, using machine learning and data science tools. To understand the impact of hashtags on reach and engagement, for example, one would download all of their Twitter data and run a statistical analysis to determine if there is a significant effect. Penn emphasizes the…
Summary In today's episode, I break down what Mastodon is and how this decentralized social platform works, from choosing a home server to standing up your own instance. Here's what this means for you. You discover a federated alternative to centralized social networks that gives you real ownership over your community, free from any single…
Mara asks, “Can you touch upon expectations of an in-house marketer has on Social Media, vs Agency, like in terms of content and KPI’s for example?” The expectations for an in-house marketer and an agency should be the same in terms of content and KPIs. The main difference is in resourcing. An employee costs less…
