Sales Prediction with Social Media Analysis
SRII Global Conference（2014）
摘要
Social media has been valuable sources to predict the future outcomes of some events such as box-office movie revenues or political elections. This paper focuses on periodic forecasting problems of product sales based on social media analysis and time-series analysis. In particular, we present a predictive model of monthly automobile sales using sentiment and topical keyword frequencies related to the target brand over time on social media. Our predictive model illustrates how different time scale-based predictors derived from sentiment and topical keyword frequencies can improve the prediction of the future sales.
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关键词
time series analysis,periodic forecasting problems,social media analytics, prediction system, sentiment analysis, topical keyword analysis, time series analysis,social media analytics,forecasting theory,automobiles,time-series analysis,marketing data processing,topical keyword frequencies,time scale-based predictors,automobile sales,sales management,sentiment frequencies,product sales prediction,prediction system,target brand,natural language processing,social media analysis,social networking (online),topical keyword analysis,sentiment analysis,time series,market research,correlation,history,predictive models,fluctuations,media
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