Recipe popularity prediction based on the analysis of social reviews

Xudong Mao; Yanghui Rao; Qing Li

doi:10.1109/ICAwST.2013.6765504

Recipe popularity prediction based on the analysis of social reviews

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

6 Citations (Scopus)

Abstract

In social based web services systems, some resources gain popularity while others do not. It would be valuable if we can predict the popularity of certain resource. In this work, we study the recipe popularity prediction problem using the Yelp dataset. We investigate various features that can be extracted and help to improve the performance. In particular, we propose to do the sentiment analysis over the reviews and treat the sentimental scores as one of the features. A polynomial regression model is developed to predict the recipe popularity. The experimental results show that our proposed method outperforms the baseline method. © 2013 IEEE.

Original language	English
Title of host publication	2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013
Publisher	IEEE Computer Society
Pages	568-572
DOIs	https://doi.org/10.1109/ICAwST.2013.6765504
Publication status	Published - 2013
Event	2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013 - Aizuwakamatsu, Japan Duration: 2 Nov 2013 → 4 Nov 2013

Conference

Conference	2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013
Place	Japan
City	Aizuwakamatsu
Period	2/11/13 → 4/11/13

Research Keywords

Popularity prediction
Regression
Sentiment analysis
Social network

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10.1109/ICAwST.2013.6765504

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Mao, X., Rao, Y., & Li, Q. (2013). Recipe popularity prediction based on the analysis of social reviews. In 2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013 (pp. 568-572). Article 6765504 IEEE Computer Society. https://doi.org/10.1109/ICAwST.2013.6765504

@inproceedings{442b8193d21d4a4c8da5eea75aa9ba2f,

title = "Recipe popularity prediction based on the analysis of social reviews",

abstract = "In social based web services systems, some resources gain popularity while others do not. It would be valuable if we can predict the popularity of certain resource. In this work, we study the recipe popularity prediction problem using the Yelp dataset. We investigate various features that can be extracted and help to improve the performance. In particular, we propose to do the sentiment analysis over the reviews and treat the sentimental scores as one of the features. A polynomial regression model is developed to predict the recipe popularity. The experimental results show that our proposed method outperforms the baseline method. {\textcopyright} 2013 IEEE.",

keywords = "Popularity prediction, Regression, Sentiment analysis, Social network",

author = "Xudong Mao and Yanghui Rao and Qing Li",

year = "2013",

doi = "10.1109/ICAwST.2013.6765504",

language = "English",

pages = "568--572",

booktitle = "2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013",

publisher = "IEEE Computer Society",

address = "United States",

note = "2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013 ; Conference date: 02-11-2013 Through 04-11-2013",

}

Mao, X, Rao, Y & Li, Q 2013, Recipe popularity prediction based on the analysis of social reviews. in 2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013., 6765504, IEEE Computer Society, pp. 568-572, 2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013, Aizuwakamatsu, Japan, 2/11/13. https://doi.org/10.1109/ICAwST.2013.6765504

Recipe popularity prediction based on the analysis of social reviews. / Mao, Xudong; Rao, Yanghui; Li, Qing.
2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013. IEEE Computer Society, 2013. p. 568-572 6765504.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Recipe popularity prediction based on the analysis of social reviews

AU - Mao, Xudong

AU - Rao, Yanghui

AU - Li, Qing

PY - 2013

Y1 - 2013

N2 - In social based web services systems, some resources gain popularity while others do not. It would be valuable if we can predict the popularity of certain resource. In this work, we study the recipe popularity prediction problem using the Yelp dataset. We investigate various features that can be extracted and help to improve the performance. In particular, we propose to do the sentiment analysis over the reviews and treat the sentimental scores as one of the features. A polynomial regression model is developed to predict the recipe popularity. The experimental results show that our proposed method outperforms the baseline method. © 2013 IEEE.

AB - In social based web services systems, some resources gain popularity while others do not. It would be valuable if we can predict the popularity of certain resource. In this work, we study the recipe popularity prediction problem using the Yelp dataset. We investigate various features that can be extracted and help to improve the performance. In particular, we propose to do the sentiment analysis over the reviews and treat the sentimental scores as one of the features. A polynomial regression model is developed to predict the recipe popularity. The experimental results show that our proposed method outperforms the baseline method. © 2013 IEEE.

KW - Popularity prediction

KW - Regression

KW - Sentiment analysis

KW - Social network

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DO - 10.1109/ICAwST.2013.6765504

M3 - RGC 32 - Refereed conference paper (with host publication)

SP - 568

EP - 572

BT - 2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013

PB - IEEE Computer Society

T2 - 2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013

Y2 - 2 November 2013 through 4 November 2013

ER -

Recipe popularity prediction based on the analysis of social reviews

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