Research On The Application Of Bass Emotion Model Based On Online Reviews In Sales Forecasting Of Fresh Products

With the continuous development of China's information technology,compared to the traditional shopping form before,online shopping has become the Internet era,and many external factors will have an impact on consumer purchasing behavior.Due to the continuous upgrade and update of the online review system in the Internet consumer platform,online reviews are currently used as an important communication medium to share shopping experiences,which can enable consumers to more conveniently and efficiently search for relevant information about products.As a result,contemporary consumers' purchase decisions are often subject to the impact of existing online reviews of the product.Online reviews have the characteristics of wide dissemination,fast speed,large amount of information,and measurability.It breaks through time and geographical restrictions,and these characteristics will affect consumers' purchasing decisions and business product sales.The development of the online review system makes online reviews an important reference for consumers' purchase decisions and ultimately affects product sales.How to accurately predict the sales volume of products has become a hot issue for enterprises now,and the issue of forecasting the sales volume of short-life-cycle products has attracted much attention of enterprises.At present,there are relatively few researches on the demand prediction of short-life-cycle products at home and abroad.The traditional forecasting methods are not designed for short-lifecycle environments and may not be suitable for the prediction of short-life-cycle products because they do not take short life Features of cycle products.In view of the above problems,this article selects the fresh produce industry and applies the Bass model to study the diffusion process of short-cycle fresh produce.Based on the online reviews of the fresh food industry,this paper analyzes the impact of online reviews,and proposes a product sales forecasting method based on online reviews analysis and Bass model.Analyze the impact of online review indicators on product sales while considering repeated purchases.Based on the adequacy of online review indicators,a product sales forecast model based on online review sentiment analysis and products based on online review multiple indicators are proposed.Sales forecast model.The first part studies the impact of online reviews on sales volume through literature research.In the second part,the text mining and Bass model are combined to extend the Bass model,consider the sentiment index of online reviews,and study the impact of online reviews on sales.Based on text mining,the sentiment index classification of online reviews is analyzed,and based on it,a fresh sales forecast model is constructed and its applicability is verified.The third part,put forward conclusion and the limition of research.Combining the impact of online reviews on sales of fresh products will help improve the accuracy of fresh product sales forecasts and provide an important basis for companies to formulate production and inventory plans and marketing strategies.Starting from sentiment analysis and sales forecasting,this paper proposes a method for forecasting sales based on online reviews,which enriches the theory,methods,and techniques of sales forecasting,and provides a basis for companies to forecast sales of short-term products.That can be used for reference.