Research And Implementation Of Warning And Response Plan System Of Web Public Sentiment

In recent years, with the rapid development of internet technology, the management of Web Public Sentiment has become an important issue of social management. It is necessary to use software system to process the massive data of Web Public Sentiment automatically. And the system can be used as an effective assistance of the administrators of Web Public Sentiment.This paper proposes an index system of Web Public Sentiment, which is the basis of further researches in this paper. Then, this paper studies the forecast methods of Web Public Sentiment. It proposes an optimization forecast model of Web Public Sentiment based on Gray Forecast Model, and then proposes an adaptive mechanism of forecast model. Both of them have achieved good results in Web Public Sentiment Forecast. Subsequently, the paper studies the decision-making problem of Web Public Sentiment’s response plans. It designs a plan library of Web Public Sentiment, and proposes an automatical decision-making model based on dedision tree model to achieve automatical decision-making of response plans of Web Public Sentiment. In addition, this paper also introduces an evaluation mechanism for forecast and decision-making model to achieve the assessment of results of forecast and decision-making in real time, which can be used to assess or amend the models.Firstly, this paper introduces the background and significance of the warning and response plan system of Web Public Sentiment, and then introduces current related research achievements. Subsequently, this paper introduces the index system of Web Public Sentiment. Then, this paper introduces the research on Web Public Sentiment Forecast methods. Next, the automatical decision-making model based on dedision tree model is introduced. Finally, on the basis of these studies, this paper introduces the design and implemention of the warning and response plan system of Web Public Sentiment, which can achieve functions of data storage, forecast, warning, response plans’ decision-making and model evaluation of Web Public Sentiment, and then sets up a test environment and performs the functional tests of the system, which proves that the system can meet all functional requirements.