Re-Evaluation of On-Line Hot Topic Discovery Model

Author(s):  
Hui-min Ye ◽  
Sushil Sharma ◽  
Huinan Xu

As a major medium for information transmission, Internet plays an important role in diffusing and spreading news on web. Some governments attach great importance and pay lot of effort trying to detect, track the development of events and forecast emergency on internet. On the basis of the researches in the field of topic detection and tracking, we proposed a model for hot topic discovery that would pick out hot topics by automatically detecting, clustering and weighting topics on the websites within a time period. We also introduced a topic index approach in following the growth of topics, which is useful to analyze and forecast the development of topics on web.

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Tongyu Zhu ◽  
Jianjun Yu

The microblogging is prevailing since its easy and anonymous information sharing at Internet, which also brings the issue of dispersing negative topics, or even rumors. Many researchers have focused on how to find and trace emerging topics for analysis. When adopting topic detection and tracking techniques to find hot topics with streamed microblogging data, it will meet obstacles like streamed microblogging data clustering, topic hotness definition, and emerging hot topic discovery. This paper schemes a novel prerecognition model for hot topic discovery. In this model, the concepts of the topic life cycle, the hot velocity, and the hot acceleration are promoted to calculate the change of topic hotness, which aims to discover those emerging hot topics before they boost and break out. Our experiments show that this new model would help to discover potential hot topics efficiently and achieve considerable performance.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 3858-3870
Author(s):  
Chuanzhen Li ◽  
Minqiao Liu ◽  
Juanjuan Cai ◽  
Yang Yu ◽  
Hui Wang

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 98044-98056
Author(s):  
Wei Liu ◽  
Lei Jiang ◽  
Yusen Wu ◽  
Tingting Tang ◽  
Weimin Li

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