On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
The Journal of Machine Learning Research
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Predicting the popularity of online content
Communications of the ACM
Empirical study of topic modeling in Twitter
Proceedings of the First Workshop on Social Media Analytics
A straw shows which way the wind blows: ranking potentially popular items from early votes
Proceedings of the fifth ACM international conference on Web search and data mining
Online social networks: A survey of a global phenomenon
Computer Networks: The International Journal of Computer and Telecommunications Networking
Characterizing the life cycle of online news stories using social media reactions
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
| Hi-index | 0.00 |
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.