User Portraits Of Popular Science Micro-Videos ——Take The Popular Science Account "S" As An Example

In the context of the all-media era,micro video is a new form for popularizing science.Popular science micro video is loved by the public for its entertainment and fun,and has become an important science resource at the moment.At the same time,with the development of new media,the role of the public has gradually changed from a traditional "audience" to a "user".Users are not only passive receivers of information,but also publishers and spreaders of information.Therefore,constructing user portraits of popular science micro-videos and understanding the demographic and behavioral characteristics of users will help the producers and spreaders understand and meet the needs and preferences of users,promote the more efficient dissemination and long-term development of popular science micro video,and make contributions to the development of popular science.Taking the popular science micro video account "S" as an example,this paper adopts three research methods: Python mining method,questionnaire survey method and in-depth interview method,to study the user portrait of the popular science micro video account "S" from the construction of group user portraits to three rounds of research,analyzes the fixed attributes and behavior attributes of the users of the popular science micro video account "S",and finally obtains the user portrait model of the popular science micro-video account "S".The paper puts forward some suggestions for improving the popular science micro video account "S".The conclusions of this study are as follows.First,the user portrait of the popular science micro-video account "S" can be constructed from two aspects of the user's fixed attributes and behavioral attributes.The fixed attributes of the user include gender,region,age structure,and Weibo sunshine.There are seven dimensions of credit and certification,education,occupation and industry.User behavior attributes include interactive behavior type,interaction mode,knowledge construction behavior in the process of interaction,attention time,attention motivation,interaction frequency,interaction motivation,Popular science preference,learning preference,popular science micro-video preference and usage behavior eleven dimensions.Second,the fixed attributes of users of the popular science micro-video account "S" are as follows:(1)The gender distribution is uneven,with more male users than female users;(2)The age structure is unevenly distributed,with users aged 21-25 being the main force(3)Uneven geographical distribution,dense users in the east and sparse users in the west;(4)Weibo users generally have better sun literacy,and there are more anonymous ordinary users;(5)the distribution of education is diversified,with undergraduate and master's users occupying the mainstream;(6)Users are mainly full-time students in occupations;(7)Education and training/scientific research institutions are the most professional in the industry.Third,the behavioral attributes of users of the popular science micro-video account "S" are as follows:(1)From the perspective of interactive behavior type,users are more inclined to forward behavior;(2)From the perspective of interactive mode,users are more inclined to single mode interaction(3)From the perspective of behavior in the knowledge construction process,users are mostly at the level of meaning negotiation,and "question-response" is the most common cognitive behavior of users;(4)From the point of view of the length of attention,the user's attention time is longer,Mostly mature users;(5)From the point of view of attention motivation,learning science and technology knowledge,entertainment,and hobby science are the main points of attention;(6)From the perspective of interaction frequency,user interaction is occasional behavior;(7)From the perspective of interaction motivation,users interact mainly for social motivation and content approval;(8)From the perspective of popular science hobbies,users have a wide range of popular science hobbies;(9)From the perspective of user learning preferences,users' learning preference diversification,like vertical learning,etc.;(10)From the view of popular science micro-video preferences,users like videos that can resonate and inspire them,etc.:(11)From the perspective of user behavior,it is better than the starting point The interactive behavior of,forwarding,and commenting,users prefer to recommend popular science micro-videos to those in need.Based on the user portrait characteristics of the popular science micro video account "S",this paper puts forward the following three suggestions for the operation and creation of the popular science micro video:(1)Popular science micro video accounts should be clearly positioned with outstanding feature;(2)Popular science micro video accounts should enhance the interactivity of the content release;(3)the popular science micro video should remain interesting and educational.