Abstract: Purpose of this paper is to use Facebook dataset for predicting Exchanges in Electronic business. For this purpose, first a dataset is collected from Facebook users and this dataset is divided into two training and test datasets. First, an advertisement post is sent for training data users and feedback from each user is recorded. Then, a learning machine is designed and trained based on these feedbacks and users' profiles. In order to design this learning machine, genetic programming is used. Next, test dataset is used to test the learning machine. The efficiency of the proposed method is evaluated in terms of Precision, Accuracy, Recall and F-Measure. Experiment results showed that the proposed method outperforms basic algorithm (based on J48) and random selection method in selecting objective users for sending advertisements. The proposed method has obtained Accuracy=74% and 73% earning ration in classifying users.

Shokooh Sheikh Abooli Poor and Mohammad Ebrahim Shiri, “A Genetic Programming based Algorithm for Predicting Exchanges in Electronic Trade using Social Networks’ Data” International Journal of Advanced Computer Science and Applications(ijacsa), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080524

@article{Poor2017,
title = {A Genetic Programming based Algorithm for Predicting Exchanges in Electronic Trade using Social Networks’ Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080524},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080524},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {Shokooh Sheikh Abooli Poor and Mohammad Ebrahim Shiri}
}