Toward Predicting Popularity of Social Marketing Messages

  • Bei Yu
  • Miao Chen
  • Linchi Kwok
Conference paper

DOI: 10.1007/978-3-642-19656-0_44

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6589)
Cite this paper as:
Yu B., Chen M., Kwok L. (2011) Toward Predicting Popularity of Social Marketing Messages. In: Salerno J., Yang S.J., Nau D., Chai SK. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2011. Lecture Notes in Computer Science, vol 6589. Springer, Berlin, Heidelberg

Abstract

Popularity of social marketing messages indicates the effectiveness of the corresponding marketing strategies. This research aims to discover the characteristics of social marketing messages that contribute to different level of popularity. Using messages posted by a sample of restaurants on Facebook as a case study, we measured the message popularity by the number of “likes” voted by fans, and examined the relationship between the message popularity and two properties of the messages: (1) content, and (2) media type. Combining a number of text mining and statistics methods, we have discovered some interesting patterns correlated to “more popular” and “less popular” social marketing messages. This work lays foundation for building computational models to predict the popularity of social marketing messages in the future.

Keywords

text categorization marketing social media prediction media type 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Bei Yu
    • 1
  • Miao Chen
    • 1
  • Linchi Kwok
    • 2
  1. 1.School of Information StudiesSyracuse UniversityUSA
  2. 2.College of Human EcologySyracuse UniversityUSA

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