Artificial intelligence in news gathering、Production、Distribution、Receive、Feedback is increasingly used in applications，It is particularly necessary to control the “algorithm” with mainstream value orientation。Today’s headlines、Tik Tok、Recommendation algorithms in platforms such as Xiaohongshu distribute and push content according to users’ existing interests，User seems to have some interest autonomy。But what needs to be paid attention to is whether and how the user's interests are affected by other users in the recommendation algorithm system，In turn, it affects the evolution of user interests in the platform。Based on this dimension，The theoretical dimension and role of “mobile bet365” in the recommendation algorithm platform need to be clearly understood theoretically and consciously、Function。Some intermediary user interests in the algorithm platform，Algorithm push that affects other users’ preferences through the algorithm system，And gradually change the interests of push "recipients"，Thus realizing the role functions of "influencer" and "actor" of interest。The push interests biased by the algorithm are affected by the key "mobile bet365" in the platform and radiate to other users in the platform。This means，The platform’s “mobile bet365” operate through the special mechanism and system of the algorithm，Influence other users in the platform to generate and develop interests。

　The connotation of "mobile bet365" on the algorithm push platform

The role and function of the "mobile bet365 leader" of the algorithm push platform mainly have the following connotations。

一，Mediation rather than directness。Algorithmic mobile bet365 are not ordinary Internet mobile bet365，They influence the way and direction in which the algorithm exerts "interest influence" on individuals through their relationship with the algorithm，So that users are seemingly pushed to cater to their interests，In fact, it is transmitted through the algorithm platform with a specific tendency、Directional interest，Thus conveying the interests of key users、Shape platform interest。

　Second，Leading rather than following。The above-mentioned functional others and intermediary users are not followers and passive parties focused on interests，Instead, it emphasizes the leading and activating aspects of interest。They are "mobile bet365"，Instead of "interested leader"。

　Third，Holistic rather than partial。What the interest leader emphasized is，What do people like、The impact of the overall “interest status” or “interest vector” of what is disliked，Rather than the impact of a certain opinion or an attitude on a certain public event，Reflects individual "interest spectrum" or "user memes"，Emphasis on the "opinion model" rather than the "opinion leader" dimension。Overall，mobile bet365’ interests spread in the algorithm platform，This leading algorithm-mediated realization of social relationships，Deliver interesting memes to other users through interaction with the algorithm。

Exploring the fundamentals，Recommendation algorithms are not just a computing technology that guesses “likes”，It is a social relationship that spreads interests between users mediated by algorithms。In this relationship，Shows who has control、How to have dominance，Involving who and how the push and mobile bet365 practices influence the algorithm to "favour" other users through this platform。

　　The role and mechanism of “mobile bet365” in algorithmic push platforms

Algorithm experts and mobile bet365。Some specific user guidance、Guide other content producers to learn the platform’s algorithm recommendation rules，Comply with its commercialization，These users can be called “algorithmic experts”。This will guide platform users to produce content that meets specific interests，It also shapes the interest characteristics of the platform。Users who are “algorithm experts” claim to know how algorithms “actually work”，Teach content producers how to calculate the value of content and format it based on platform metrics，Encourage users as content producers to build and manage audiences。Foreign scholars conduct digital anthropological analysis of cases，Published on Facebook、The concept of “algorithmic activists” in platforms such as Twitter，“Algorithmic experts” use the knowledge of algorithms in media platforms to make programmed choices as a proxy for human judgment，To achieve their political goals，Help them spread their message and increase their popularity。From “opinion leader” to “algorithm expert”，Reflects the major differences in the models of "influencers" in traditional media and algorithmic media。

Visible users and mobile bet365。The user’s degree of “visibility” in the algorithm，Related to the extent to which their interests are communicated to the algorithm，This is related to the effect of the user or the user group spreading their interests to other users through the intermediary of the algorithm。Some foreign scholars pointed out，Vloggers on YouTube have different visibility levels in the algorithm，Algorithm favors the middle class、Actors who meet the advertiser’s requirements，Its highly successful vloggers will also benefit from YouTube’s algorithmic visibility。A small group of users with high visibility，It may even affect the algorithm’s interest in recommendation methods and recommendation preferences for the entire platform。Users with high visibility in the algorithm，Become a certain popular type，Enable users to follow them to produce content。This prompts users to gradually understand the culture and participation rules of the online platform，And start predicting popular genres and modifying your own content releases。

High connectivity and mobile bet365。In recommendation system，Users and their friends are more likely to have the same interests，The recommendation system takes advantage of this social relationship for filtering and recommendation；This mechanism in turn affects the evolution of user interests。Experimental results on a movie rating dataset，A dominant group will contribute more neighbors in collaborative filtering recommendation generation，and influence the algorithm’s predictions by virtue of its presence in these groups，Recommendation algorithms prioritize the preferences of dominant groups，Also amplifies all users’ biases against dominant groups。Have stronger social connections、Socially homogeneous individuals，It is easier to get recommendations to other users under the influence of the algorithm，Generate more connections in the algorithm platform，Their interests and preferences are also more likely to radiate to other users。Interest filtering brought by social filtering、Interest preferences of special groups in the platform，will be transmitted to other users。This reflects highly connected users、How important node individuals have the possibility of becoming an interest leader on the algorithm platform。

Active feedback and mobile bet365。Platform recommendations will amplify the interests of active users in “algorithm feedback”。Confirmed after analyzing the Twitter data set，The performance of each algorithm is highly dependent on active users；When active users change，Recommendation hit rate will show a high deviation。Based on research into political comments from German users and posts from political parties，Hyperactive users will strongly affect the recommendation system；As hyperactive users asymmetrically influence the popularity of political content，Recommendation algorithms may also replicate this asymmetry。People who have less feedback on the algorithmic system are more likely to be forced to become similar to the "active users" in the algorithmic system。Hyperactive users also create an iterative loop in the algorithmic system，Continuously amplify the influence and diffusion of the interests of previously active users on the interests of other users on the platform。

“mobile bet365” in the algorithm platform bring algorithm push，From doing what others like to pretending to do what they want、From personalized interests to non-personalized interests、From intermediary agency to intermediary individual、The theoretical model and propagation characteristics from one-way action of algorithms to two-way circulation。The role of mobile bet365 in the algorithm platform，From algorithm catering、Algorithm Visibility、Social filterability、User similarity、Main dimensions such as feedback activity。They produce imprecise data alienation and paradox logic after precise calculation by algorithms，Constraints on accuracy of recommendation via algorithm，Deviations and contradictions in recommendation satisfaction，Distorting the user’s interest in the recommendation relationship、Interest discount、Fake interest and other consequences。Users seem to have “freedom of interests”，However, this kind of freedom of interest is "pseudo-freedom" under the multiple two-way cycle of "algorithm ← → intermediary user ← → user"。Opinion leaders in the traditional media era and mobile bet365 in the algorithmic media era，There are fundamental differences in ontology and methodology，We cannot look at the influence model of future platform users in the "rearview mirror" of the pre-algorithm era。Identification of mobile bet365、Adjustment applied to the guidance of algorithmic era and network culture、Management and Development，Is an important issue with theoretical potential and practical value。

(Author’s unit: School of Art and mobile bet365, Tongji University)