Real-Time Monitoring of Smart Campus and Construction of Weibo Public Opinion Platform

With the development and penetration of information technology, the “fourth media”-the network media is coming, and the “grievance crisis” is increasingly happening. The effective monitoring of online public opinion information becomes a problem. For each university, how to understand the sensation of teachers and students in real time in the era of informationization entering the intelligent campus has become an urgent problem for all colleges and universities. This paper first analyzes the characteristics of Weibo’s communication and the process of microblogging’s public opinion formation, the mechanism of communication, and so on. For the acquisition of this information, the reptile method was used to obtain the required data, which was beneficial to the real-time sensation in the smart campus. Then, based on the improved single-pass algorithm to analyze the new characteristics of microblog propagation information and the public opinion sent by college students, and compared the improved single-pass algorithm with the effect of single-pass algorithm, the improved algorithm had the recall rate was high, the false detection rate was low, and the running time was short. Finally, taking the lyrics of college teachers and students as the research object, unified modeling language modeling was used to analyze the public opinion monitoring platform of the smart campus, and the campus public opinion of several major events was monitored and analyzed. This provided a reference for the effective, intelligent, and real-time detection of Weibo public opinion in colleges and universities.

[1]  Ai-Min Yang,et al.  Research on a Fusion Scheme of Cellular Network and Wireless Sensor for Cyber Physical Social Systems , 2018, IEEE Access.

[2]  Song Jiang,et al.  Ensemble Prediction Algorithm of Anomaly Monitoring Based on Big Data Analysis Platform of Open-Pit Mine Slope , 2018, Complex..

[3]  Jianhui Wu,et al.  Differential Diagnosis Model of Hypocellular Myelodysplastic Syndrome and Aplastic Anemia Based on the Medical Big Data Platform , 2018, Complex..

[4]  Young-Woo Seo,et al.  Text clustering for topic detection , 2004 .

[5]  Zhaoxing Li,et al.  Research on Big Data Digging of Hot Topics about Recycled Water Use on Micro-Blog Based on Particle Swarm Optimization , 2018, Sustainability.

[6]  Jie Li,et al.  Dynamic Prediction Research of Silicon Content in Hot Metal Driven by Big Data in Blast Furnace Smelting Process under Hadoop Cloud Platform , 2018, Complex..

[7]  Abdul Majid,et al.  Application of Parallel Vector Space Model for Large-Scale DNA Sequence Analysis , 2018, Journal of Grid Computing.

[8]  Chen Huang,et al.  Microblogging after a major disaster in China: a case study of the 2010 Yushu earthquake , 2011, CSCW.

[9]  Kate Niederhoffer,et al.  The Origin and Impact of CPG New-Product Buzz: Emerging Trends and Implications , 2007, Journal of Advertising Research.

[10]  Hao Zhang,et al.  Systematic Research on the Application of Steel Slag Resources under the Background of Big Data , 2018, Complex..

[11]  Yong Yu,et al.  News comments generation via mining microblogs , 2012, WWW.

[12]  Tingting Wang,et al.  Research on Workshop-Based Positioning Technology Based on Internet of Things in Big Data Background , 2018, Complex..

[13]  Sihem Amer-Yahia,et al.  MAQSA: a system for social analytics on news , 2012, SIGMOD Conference.

[14]  Yifan Li,et al.  Security Control Redundancy Allocation Technology and Security Keys Based on Internet of Things , 2018, IEEE Access.