Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The rumor detection problem on social network has attracted considerable attention in recent years. Most previous works focused on detecting rumors by shallow features of messages, including content and blogger features. But such shallow features cannot distinguish beten rumor messages and normal messages in many cases. Therefore, in this paper  propose an automatic rumor detection method based on the combination of new proposed implicit features and shallow features of the messages. The proposed implicit features include popularity orientation, internal and external consistency, sentiment polarity and opinion of comments, social influence, opinion retet influence, and match degree of messages. Experiments illustrate that our rumor detection method obtain significant improvement compared with the state-of-the-art approaches. The proposed implicit features are effective in rumor detection on social network.
['Qiao Zhang', 'Shuiyuan Zhang', 'Jian Dong', 'Jinhua Xiong', 'Xueqi Cheng']
I am writing a research paper on a idea Automatic Detection of Rumor on Social Network
[{"from": "human", "value": "I am writing a research paper on a idea Automatic Detection of Rumor on Social Network"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The rumor detection problem on social network has attracted considerable attention in recent years. Most previous works focused on detecting rumors by shallow features of messages, including content and blogger features. But such shallow features cannot distinguish beten rumor messages and normal messages in many cases. Therefore, in this paper  propose an automatic rumor detection method based on the combination of new proposed implicit features and shallow features of the messages. The proposed implicit features include popularity orientation, internal and external consistency, sentiment polarity and opinion of comments, social influence, opinion retet influence, and match degree of messages. Experiments illustrate that our rumor detection method obtain significant improvement compared with the state-of-the-art approaches. The proposed implicit features are effective in rumor detection on social network."}]