Opinion spammer detection in web forum
Journal
38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages
759-762
ISBN
9781450336215
Date Issued
2015
Author(s)
Chen Y.-R.
Abstract
In this paper, a real case study on opinion spammer detection in web forum is presented. We explore user profiles, maximum spamicity of first posts of users, burstiness of registration of user accounts, and frequent poster set to build a model with SVM with RBF kernel and frequent itemset mining. The proposed model achieves 0.6753 precision, 0.6190 recall, and 0.6460 F1 score. The result is promising because the ratio of opinion spammers in the test set is only 0.98%.
Subjects
Fake web review
Opinion spammer detection
Web forum
Type
conference paper