Recipe popularity prediction based on the analysis of social reviews

Xudong Mao, Yanghui Rao, Qing Li

Research output: Unpublished conference presentation (presented paper, abstract, poster)Conference presentation (not published in journal/proceeding/book)Academic researchpeer-review

3 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.

Original languageEnglish
Pages568-572
Number of pages5
DOIs
Publication statusPublished - 1 Jan 2013
Externally publishedYes
Event2013 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 20134 Nov 2013

Conference

Conference2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013
CountryJapan
CityAizuwakamatsu
Period2/11/134/11/13

Keywords

  • Popularity prediction
  • Regression
  • Sentiment analysis
  • Social network

ASJC Scopus subject areas

  • Software

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