If you ask what has been the Whatsapp Database biggest change in WeChat in the past year or two, my answer must be - WeChat has finally begun to embrace algorithmic distribution! From being obsessed with "social distribution" to starting to Whatsapp Database embrace "algorithmic distribution", this is an amazing change. This is an important iteration and evolution of WeChat on the road, and the logic behind this change is also worth every Internet person to think deeply about ! 1. Changed WeChat content distribution logic Obviously, Zhang Xiaolong didn't like algorithms at first.
To be precise, at the beginning of the WeChat story, Zhang Xiaolong was very afraid of the algorithm involved in content distribution, which Whatsapp Database can be reflected in many aspects: The order of the circle of friends is always only in chronological order; The ordering of public numbers is always in time sequence; There has Whatsapp Database never been a recommendation, guess you like, popular and other algorithm intervention modules anywhere in WeChat; WeChat’s improvement of the reading experience of the official account has only changed from a list of official accounts to a list of contents; All the content you see on WeChat is the result of your personal, active choices.
However, today, the situation has undergone a great change, and algorithm distribution has begun to penetrate into all aspects of Whatsapp Database WeChat content ecology in multiple dimensions—— Take a look: Take a look at the launch of algorithm-based recommendations for "featured"; Video ID: The video ID has the tag "Popular" calculated by the algorithm; Whatsapp Database Official account sorting: The articles of the official account are no longer sorted purely in time series, but are optimized and sorted through algorithms; Official account recommendation: In the official account information flow, the algorithm recommends the official account you may like; Official account article recommendation: At the end of the official account article, the algorithm recommends articles related to the topic;