Welcome to Francis Academic Press

Academic Journal of Computing & Information Science, 2020, 3(1); doi: 10.25236/AJCIS.2020.030116.

Research on Network Video Hot Event Discovery System


Ying Li*, Jiale Yuan

Corresponding Author:
Ying Li

New Media College, Communication University of Zhejiang, Hangzhou, China
*Corresponding author email:[email protected]


In this paper, the network video hot event discovery system integrates domestic mainstream network video website data (e.g. Youku, Tudou, Ku6, etc.) and Internet TV data. This research studies the bottom layer of network video multi-source information extraction, filtering, aggregation, storage, etc. To realize video semantic analysis and processing, the research further studies the multi-layer semantic unified representation model of multi-source heterogeneous video data. On this basis, aiming at providing decision support for government departments to monitor video public opinion and emergency intervention, the research also studies network emergency discovery technology, hot event real-time tracking technology, and hot development trend prediction technology. Finally, relying on the above research results, the research develops a cloud computing-based network video hot event monitoring and analysis system and then demonstrates the application in network media.


Public Opinion Analysis; Hot Events; Network Video

Cite This Paper

Ying Li, Jiale Yuan. Research on Network Video Hot Event Discovery System . Academic Journal of Computing & Information Science (2020), Vol. 3, Issue 1: 150-159. https://doi.org/10.25236/AJCIS.2020.030116.


[1] Chen Si, Lu Qinghe, Ma Xiaoyi: The breaking point, pain point and inflection point of China's network video development, Contemporary Communication, 2019 (3): 56-58+69
[2] Zaïane O R, Han J, Li Z N, et al. MultiMediaMiner: a system prototype for multimedia data mining[C]//ACM SIGMOD Record. ACM, 1998, 27(2): 581-583.
[3] Yang Fuzheng, Wan Shuai. Research status and development trend of network video quality assessment technology [J]. Journal of Communications, 2012, 33 (4): 107-114.
[4] Matsumoto Y, Uchida H, Hagimoto M, et al. Manycore processor for video mining applications[C]//Design Automation Conference (ASP-DAC), 2013 18th Asia and South Pacific. IEEE, 2013: 574-575.
[5] Liu J, Javed O, Cheng H, et al. Detecting Complex Events from Big Video Data[J]. E-LETTER, 2013, 15(5).
[6] Jenner M. Is this TVIV? On Netflix, TVIII and binge-watching[J]. New Media &Society, 2014: 1461444814541523.
[7] J.Allan. Introduction to Topic Detection and Tracking in Topic Detection and Tracking:Event-based Information Organization[R]. Kluwer Academic Publishers,2002:1-16.
[8] Hong Yu, Zhang Yu, Liu Ting, etc. Evaluation and research review of topic detection and tracking [J] Journal of Chinese Information Processing, 2007,21 (6): 71-87.
[9] Guo Jianyong, Cai Yong, Zhen Yanxia. Topic discovery based on text clustering technology. Computer Engineering and Design [J], 2008 (6): 1426-1432.
[10] Huang Xiaobin, Zhao Chao. Application of Text Mining in the Analysis of Internet Public Opinion Information. Information Science [J], 2009 (1): 94-99.
[11] Zhao Xujian, Yang Chunming, Li Bo, Zhang Hui, Jin Peiquan, Yue Lihua, Dai Wenkai. A news topic evolution mining method based on feature evolution [J]. Chinese Journal of Computers, 2014 (4): 819-832.
[12] Huang He. Sentiment analysis of Sina Weibo based on semantic sentiment space model. International Conference on Management Science and Engineering (ICMSE'13)[C], 2013: 206-211.
[13] J. Bollen, H. Mao and X. Zeng. Twitter mood predicts the stock market. Journal of Computational Science[J], 2011, 2(1): 1-8.
[14] Yang Liang, Lin Yuan, Lin Hongfei, Discovery of Hot Events on Weibo Based on Sentiment Distribution, Journal of Chinese Information, 2012 (1): 84-90
[15] Jiang Shenghong. The formation and development, status quo and guidance of public opinion hots on the Internet [J] .Theory Monthly, 2008 (4): 34-36.
[16] Tao Jianjie. Improving the emergency response mechanism of network public opinion linkage. Party and government forum [J], 2007 (9): 28-30.
[17] Liu Yi. Internet public opinion and the transformation of government governance paradigm. Frontier [J], 2006 (10): 140-143.
[18] Wang Wei, Li Ruiguang, Zhou Yuan, Yang Wu. Microblog burst topic propagation prediction algorithm based on user and node scale [J]. Journal of Communications, 2013 (S1): 84-91.
[19] Li Biao: Research on the Spatial Structure and Characteristics of Internet Event Communication——Taking 40 Internet Hot Events in Recent Years as an Example, Journalism and Communication Research, 2011 (3): 90-99.
[20] Li Biao: Research on the Stages and Thresholds of the Dissemination of Internet Events—Taking 34 hot Internet public opinion events in 2010 as an example, International Press 2011 (10): 22-27
[21] Zhong Ying, Yu Xiucai, Analysis of Major Internet Public Opinion Events and Their Transmission Characteristics from 1998 to 2009, Journalism and Communication Research, 2010 (4): 45-52