Social Media News to Know: Monthly Roundup

Social Media News to Know: December

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Social Media News to Know - BannerTripepi Smith’s Always-Be-Learning (#ABL) culture drives us to stay up to speed on constantly changing social media platforms. This knowledge empowers our team to track, interpret and adapt to the latest and greatest social media trends on behalf of the public agencies we serve. The following is the latest installment of our regular roundup of social media news you need to know: 

  1. LinkedIn has introduced new updates for those creating newsletters on their platform from improved creation to customization tools. LinkedIn has added duplicate draft templates, enabling creators to streamline their creation process by replicating previous formats. LinkedIn is also adding newsletter analytics, including additional performance notes and audience demographics. 
  2. After five years in the works, Meta has launched an end-to-end encryption (E2E) by default on Messenger for users. This means there is an extra layer of security provided to users. This shift to full encryption by default moves Messenger more in line with WhatsApp where messages and calls are protected from the moment they leave the device to the receiver’s device.
  3. X (Twitter) is promoting opportunities in ‘Q5’ which is being covered in the post-Christmas to mid-January period. During this time, there will be reduced cost-per-mille (CPMs) and cost-per-conversation as consumers shop for post-holiday deals. This will allow marketers to reach a larger audience at a lower cost with their promotions. 
  4. Meta has implemented more generative AI elements such as post-prompts and image creation in-stream. One of the new features includes the “Imagine” text-to-image tool, another way to generate visuals. Meta is also expanding the capacity of the “Imagine” in chat, so users can refine custom visuals in-stream. 
  5. Meta has launched a new initiative to establish AI safety regulations. The project called “Purple Llama” was developed with the intent of creating parameters around cybersecurity considerations and input/output safeguards in the development of large language models (LLMs) and generative AI tools. This will allow communities to build responsibly with open generative AI models. 

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