TY - JOUR
T1 - User-generated content on social media
T2 - Predicting market success with online word-of-mouth
AU - Liu, Yong
AU - Chen, Yubo
AU - Lusch, Robert F.
AU - Chen, Hsinchun
AU - Zimbra, David
AU - Zeng, Shuo
PY - 2010
Y1 - 2010
N2 - Online social media, a user-generated content or online word of mouth (WOM), which allows consumers to share their product opinions and experience and has the potential to influence product sales and firm strategy, is studied in context of the Hollywood movie industry. An online WOM information was collected from the message board of Yahoo Movies for a total of 257 movies released from 2005 to 2006. SentiWordNet and OpinionFinder, two lexical packages of computational linguistics, were used to construct the sentiment measures for the WOM data. Results show that WOM communication starts early in the preproduction period, becomes highly active before movie release, and diminishes as the movie is shown for more weeks in theaters. A movie that receives more active WOM communication tends to receive higher evaluations from movie critics, suggesting the number of messages could work as a signal for product quality.
AB - Online social media, a user-generated content or online word of mouth (WOM), which allows consumers to share their product opinions and experience and has the potential to influence product sales and firm strategy, is studied in context of the Hollywood movie industry. An online WOM information was collected from the message board of Yahoo Movies for a total of 257 movies released from 2005 to 2006. SentiWordNet and OpinionFinder, two lexical packages of computational linguistics, were used to construct the sentiment measures for the WOM data. Results show that WOM communication starts early in the preproduction period, becomes highly active before movie release, and diminishes as the movie is shown for more weeks in theaters. A movie that receives more active WOM communication tends to receive higher evaluations from movie critics, suggesting the number of messages could work as a signal for product quality.
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U2 - 10.1109/MIS.2010.27
DO - 10.1109/MIS.2010.27
M3 - Article
SN - 1541-1672
VL - 25
SP - 75
EP - 78
JO - IEEE Intelligent Systems
JF - IEEE Intelligent Systems
IS - 1
M1 - 5432262
ER -