application of artificial neural network in social media data analysis a case of lodging business in philadelphia文档.pdf
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application of artificial neural network in social media data analysis a case of lodging business in philadelphia文档
Application of Artificial Neural Network
in Social Media Data Analysis: A Case
of Lodging Business in Philadelphia
Thai Le, Phillip Pardo and William Claster
Abstract Artificial Neural Network (ANN) is an area of extensive research.
The ANN has been shown to have utility in a wide range of applications. In this
chapter, we demonstrate practical applications of ANN in analyzing social media
data in order to gain insight into competitive analysis in the field tourism. We have
leveraged the use of an ANN architecture in creating a Self-Organizing Map
(SOM) to cluster all the textual conversational topics being shared through thou-
sands of management tweets of more than ten upper class hotels in Philadelphia. By
doing so, we are able not only to picture the overall strategies being practiced by
those hotels, but also to indicate the differences in approaching online media among
them through very lucid and informative presentations. We also carry out predictive
analysis as an effort to forecast the occupancy rate of luxury and upper upscale
group of hotels in Philadelphia by implementing Neural Network based time series
analysis with Twitter data and Google Trend as overlay data. As a result, hotel
managers can take into account which events in the life of the city will have deepest
impact. In short, with the use of ANN and other complementary tools, it becomes
possible for hotel and tourism managers to monitor the real-time flow of social
media data in order to conduct competitive analysis over very short timeframes.
Keywords Artificial neural networks (ANNs) Hospitality Social Media anal-
ysis Kohonen Forecasting Competitive Analysis Lodging Hotel Occupancy
T. Le () P. Pardo W. Claster
Ritsumeikan Asia Pacific University, Jumonji Baru 1-1, Beppu, Oita, Japan
e-mail: le.thai.jp@
P. Pardo
e-mail: pardorit@apu.ac.jp
W. Claster
e-mail: wclaster@apu
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