The Social Media Big Data Analysis for Demand Forecasting in the Context of Globalization

Author:

Gao Yifang1,Wang Junwei2,Li Zhi2,Peng Zengjun2

Affiliation:

1. College of Art Design, Shanghai Jian Qiao University, China

2. School of Media and Law, NingboTech University, China

Abstract

This paper aims to analyze the predictive effect of artificial intelligence on user demand in big data social media and to provide suggestions for developing enterprise innovation frameworks and implementing marketing strategies. In response to the inconsistency between the supply of enterprise products and services and market demand, deep learning algorithms have been introduced using social media big data analysis. This algorithm has been improved to construct a user demand prediction model in social media big data based on bidirectional long short-term memory (BiLSTM) fused with Word2Vec. The model uses data acquisition and pre-processing, Word2Vec algorithm to vectorization the data information, and BiLSTM network to model and train the sequence. Finally, the model is evaluated as an example.

Publisher

IGI Global

Subject

Strategy and Management,Computer Science Applications,Human-Computer Interaction

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