Prediction method of television play on-demand amount based on network data

Abstract

The invention discloses a prediction method of television play on-demand amount based on network data. The prediction method is characterized in that the grabbed micro-blog numbers and the search times as well as related data of television plays are calculated by using a correlation analysis and single variable linear regression to obtain an initial features set, then a stepwise regression method is carried out on the initial feature set to obtain a feature set X and a feature set X, a multiple linear regression method is carried out on the feature set X and the feature set X to respectively obtain two prediction models before and after premieres of the television plays, then rankings of the television plays are predicted according to the sizes of predicted values. Compared with the prior art, according to the prediction method disclosed by the invention, the episode average on-demand amount of the television plays in an on-demand system in a period of the future time is predicated in advance, predicted results effectively reflect the popularity degree of the television plays, and the method is simple and good in accuracy, so that the basis can be provided for video operators on a decision of television play broadcast copyright purchase, and the strong support is provided for an online on-demand system on attracting users and increasing advertisement click rate.

Description

technical field [0001] The invention relates to the technical field of Internet information search, in particular to a method for predicting the volume of TV drama demand based on Sina Weibo and Baidu search network data. Background technique [0002] Prediction of video-on-demand volume has an important application in the field of network data mining. TV dramas with high on-demand volume can increase the volume of advertisements. Predicting the volume of on-demand TV dramas in advance has been widely used in advertising business expansion. Using Sina Weibo and Baidu search index to predict the on-demand volume of TV dramas in the on-demand system in a certain period of time after they go online, and the connection between TV dramas and social networks has become a research hotspot. In particular, the forecasting of the TV series on-demand volume in the online VOD system through network data has played a certain role in decision-making for video operators to purchase TV seri...

AI Technical Summary

Problems solved by technology

In the prediction method based on network data, the traditional method mainly predicts the box office of the movie. Compared with the box office prediction of the movie, the number of TV dramas on demand is affected by more factors, and does not consider the social network and search data at different times. Differences in Reflection Levels of TV Drama Views by Point-to-Point

[0004] The existing technology cannot predict the on-demand volume before the TV series goes online, and does not predict the on-demand volume through social network and search engine data at the same time.

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