• DocumentCode
    1785277
  • Title

    Sales Prediction with Social Media Analysis

  • Author

    Hyung-Il Ahn ; Spangler, W. Scott

  • Author_Institution
    IBM Res. - Almaden, San Jose, CA, USA
  • fYear
    2014
  • fDate
    23-25 April 2014
  • Firstpage
    213
  • Lastpage
    222
  • Abstract
    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.
  • Keywords
    automobiles; forecasting theory; marketing data processing; natural language processing; sales management; social networking (online); time series; automobile sales; periodic forecasting problems; product sales prediction; sentiment frequencies; social media analysis; target brand; time scale-based predictors; time-series analysis; topical keyword frequencies; Correlation; Fluctuations; History; Market research; Media; Predictive models; Time series analysis; prediction system; sentiment analysis; social media analytics; time series analysis; topical keyword analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Conference (SRII), 2014 Annual SRII
  • Conference_Location
    San Jose, CA
  • Type

    conf

  • DOI
    10.1109/SRII.2014.37
  • Filename
    6879684