Network Public Opinion Monitoring System For Agricultural Based On Hadoop

With the rapid development of Internet technology and growing number of internet users, the Internet has become the largest new media and public opinion front. The development of technology has brought a variety of expression freedom to the public and public opinion about agriculture has gone deeply into daily life and government public administration with increasing social impact. Agriculture concerns with the people’s livelihood, network passes public opinion. There is an urgent need to improve the capacity of monitoring public opinion on the internet to guide correct public opinion, to stop the spread of bad words. This paper aims to develop a multi-functional, comprehensive, effective and efficient agricultural network public opinion monitoring service platform, tracking hot topics, monitoring sensitive information, preventing negative emotions in time, guiding public opinion correctly, to provide an accurate and effective integrated platform of internet public opinion data service for government and enterprises.Firstly, the paper described the background and research status of network public opinion monitoring and elaborated the theory and key technologies in the implementation process, and made outline design and detailed design of the system on the basis of needs analysis, and focused on the design and implementation process of the system function module. Secondly, on the base of analysis of existing network monitoring systems and new internet technology, we presented the work process of founding topic, tracking topic and warning on public opinion by collecting agricultural security-related information from internet as data source integrating search engine Nutch and search application server Solr, and proposed agriculture-related hot topics discovery algorithm to improve the accuracy and efficiency of the topics found. The system has been deployed in Hadoop distributed system platform based on cloud computing environment and solved problems such as low scalability and computing efficiency of storage space of agriculture-related public sentiment internet monitoring system using Hadoop distributed ability of processing massive data to provide theoretical support and decision making basis for government and enterprises.Finally, the implementation process has been detailed including the information collection module, the information processing module, the public sentiment analysis module and the government module. The function module implementation process of the public sentiment analysis has been focused. The experiments and practical application show that the system is able to collect and update agriculture security-related information to discover new topics, judge hot topics and issue a warning notice. The paper provided an effective solution to discover new topics and issue warnings in massive data. It is very important to guide online public opinion, to listen to public opinion, to grasp the ideological trends of the people and to make early decision response. Implementation proves that the system is operating properly and can be effectively monitored to achieve the design goal.