Research And Implementation Of The Visualization Subsystem For Hot Topics In Social Networks

With the development of Internet technology in recent years,social networks are gaining their importance and prevalence in online activities.People are more dependent on social networks such as QQ Space,Renren,Moment,Facebook and LinkedIn.Social network is a network based on real world interpersonal relationships and a tool with which people communicate in reality.However,the spread of information in social networks is very different from it used to be in traditional networks.Social networks are not limited by geographical distances between people,which make the spread faster and wider,and tend to be more disordered and chaotic.However,as a subset of real-world interpersonal relationships,social networks inherit some characteristics of human network.Meaningful data and trends can be found by analyzing the characteristics in question.In this paper we propose a visualization subsystem for hot topics in social networks.The subsystem is able to discover potential information hidden in social networks which used to be scattered and chaotic.The system analyses relevant information and enables is to be easily accessed by a Web chart.The system uses Ajax to implement asynchronous interaction of front end and background,ensures front end pages can be refreshed locally.The system also utilizes Echart.js and Highchart.js to achieve intuitive display of data information as well as the advancement of the system.The research of front end visualization system contains two parts:design of interface database and front end display.The interfaces and statistics of database are optimized for many information aims in demand analysis to ensure quick and easy data accessing.In front end development we utilizes Bootstrap framework.By adopting modularized development method,we create an excellent user experience and a succinct,understandable code.Also,the system can load scripts when needed.To clarify statistical indicators,we propose statistical algorithms for each indicator.We completely tested the system to ensure its availability and stability.