Toward Predicting Popularity of Social Marketing Messages

被引：0

作者：

Yu, Bei ^{[1
]}

Chen, Miao ^{[1
]}

Kwok, Linchi ^{[2
]}

机构：

[1] Syracuse Univ, Sch Informat Studies, Syracuse, NY 13244 USA

[2] Syracuse Univ, Coll Human Ecol, Syracuse, NY 13244 USA

来源：

SOCIAL COMPUTING, BEHAVIORAL-CULTURAL MODELING AND PREDICTION | 2011年 / 6589卷

关键词：

text categorization; marketing; social media; prediction; media type;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：317 / +

页数：2

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