Application of Time Series Analyses in Big Data: Practical, Research, and Education Implications

2017 ◽  
Author(s):  
Zabihollah Rezaee ◽  
Alireza Dorestani ◽  
Sara Aliabadi
2017 ◽  
Vol 15 (1) ◽  
pp. 183-197
Author(s):  
Zabihollah Rezaee ◽  
Alireza Dorestani ◽  
Sara Aliabadi

ABSTRACT The application of Big Data and time series models is currently at an early stage. This paper examines the relevance and use of time series analyses for Big Data and business analytics by discussing the emergence of Big Data in business, presenting time series models, and providing an example of how time series models can be efficiently and effectively applied in accounting and auditing using Big Data. Using sophisticated Big Data and time series models, millions of transactions can be searched to spot patterns and detect abnormalities and irregularities. The time series model and Big Data analysis presented in this paper provide policy, practical, educational, and research implications. Businesses and management can use our suggested time series model and Big Data analysis in their predictive models of managerial strategies, decisions, and actions. Business schools and accounting programs can integrate the time series model, Big Data, and data analytics into business and accounting education.


Author(s):  
Daniel W. Capron ◽  
Rita Andel ◽  
Martin Voracek ◽  
Benedikt Till ◽  
Thomas Niederkrotenthaler ◽  
...  

Author(s):  
Petrus Mursanto ◽  
Ari Wibisono ◽  
Wendy D.W. T. Bayu ◽  
Valian Fil Ahli ◽  
May Iffah Rizki ◽  
...  
Keyword(s):  
Big Data ◽  

2012 ◽  
Vol 29 (4) ◽  
pp. 359-375 ◽  
Author(s):  
Freya Bailes ◽  
Roger T. Dean

this study investigates the relationship between acoustic patterns in contemporary electroacoustic compositions, and listeners' real-time perceptions of their structure and affective content. Thirty-two participants varying in musical expertise (nonmusicians, classical musicians, expert computer musicians) continuously rated the affect (arousal and valence) and structure (change in sound) they perceived in four compositions of approximately three minutes duration. Time series analyses tested the hypotheses that sound intensity influences listener perceptions of structure and arousal, and spectral flatness influences perceptions of structure and valence. Results suggest that intensity strongly influences perceived change in sound, and to a lesser extent listener perceptions of arousal. Spectral flatness measures were only weakly related to listener perceptions, and valence was not strongly shaped by either acoustic measure. Differences in response by composition and musical expertise suggest that, particularly with respect to the perception of valence, individual experience (familiarity and liking), and meaningful sound associations mediate perception.


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