View app
1.0.0
Shixiang app is an excellent software that integrates short videos, social networking, and recommendations. It not only has accurate recommendation algorithms and rich social experience, but also has many excellent creative videos that are worth downloading and using. It has gathered a large number of outstanding creators. It brings more visual feast and social fun to users.
1. Their works cover various fields, from funny to inspirational, from food to travel, with new creative content updated every day;
2. Relevant videos will be recommended based on the user’s preferences and interests, allowing users to discover interesting content more quickly;
3. Not only basic interaction methods such as likes and comments are available, but there are also various methods such as personalized emoticons and barrage interactions.
1. Users can record and edit their own videos, and perform various operations such as editing and filtering the videos;
2. It can recommend relevant videos based on users’ interests and behavior history, and also supports users to find videos based on search keywords;
3. Support users to share their videos to social platforms, and also have a message reminder function so that users can receive the latest likes, comments and other messages.
1. Supports various social methods such as barrage interaction and personalized emoticons, allowing users to experience more social fun;
2. The recommendation algorithm can make accurate recommendations based on the user’s behavior history and interests, allowing users to find interesting content faster;
3. It brings together many outstanding creators at home and abroad, allowing users to see more creative videos and experience more social fun.
1. It is a very easy-to-use short video social software with rich and colorful social experience and accurate recommendation algorithm;
2. The creative video content is very rich and diverse, allowing users to see more interesting and interesting videos;
3. The recommendation algorithm is very accurate and can quickly recommend content that users are interested in based on their interests and behavior history.
