The invention provides a method for hotspot discovery and evolution situation analysis in a network forum, using a crawler program to extract the HTML text of all posts in a forum; extracting pageviews and replies from each post text to form a binary group, assuming the first The binary group of the i post is (xi, yi); use the formula to calculate the score of the i-th post; obtain a popular post, and count the number of replies that occur every day from the topic posting to the capture time according to the reply record to get the binary group . The fitting effect and evaluation index are listed below: SSE=1.548e+07. SSE is the sum of squares of the error term, which reflects the discrete state of each observation value of each sample, and is also called the sum of squares within the group or the sum of squares of the residual error. R-square = 0.8339. R-square is the fitting coefficient, the larger the value, the better the fitting degree. RMSE = 525.7. RMSE is the root mean square error, which can be used as a numerical indicator to measure the measurement accuracy. After analyzing these indicators, it can be seen that the fitting effect is relatively ideal. Find the largest extreme point as x0=14; take x1=15>x0, y'(x0)<0, so the popularity of this post is declining.