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
Link To Document :
بازگشت