Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Social behaviors such as retetings, comments or likes are valuable information for human activities analysis.  focus here on user's reteting behavior which has been considered as a key mechanism of information diffusion in social networks. Since  can only observe on which messages user retet. It is a typically one-class setting which only positive examples or implicit feedback can be observed. Hover, few research works on reteting prediction consider one-class setting. ,  analyze and study the fundamental factors that might affect retetability of a tet, and then employ one-class collaborative filtering method by quantitatively measure the user personal preference and social influence beten users and messages to predict user's reteting behavior. Experimental results on a real-world dataset from social network show that the proposed method is effective and can improve the performance of the one-class collaborative filtering over baseline methods through leveraging ighted negative examples information.
['Bo Jiang', 'Jiguang Liang', 'Ying Sha', 'Rui Li', 'Wei Liu', 'Hongyuan Ma', 'Lihong V. Wang']
I am writing a research paper on a idea Retweeting Behavior Prediction Based on One-Class Collaborative Filtering in Social Networks
[{"from": "human", "value": "I am writing a research paper on a idea Retweeting Behavior Prediction Based on One-Class Collaborative Filtering in Social Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Social behaviors such as retetings, comments or likes are valuable information for human activities analysis.  focus here on user's reteting behavior which has been considered as a key mechanism of information diffusion in social networks. Since  can only observe on which messages user retet. It is a typically one-class setting which only positive examples or implicit feedback can be observed. Hover, few research works on reteting prediction consider one-class setting. ,  analyze and study the fundamental factors that might affect retetability of a tet, and then employ one-class collaborative filtering method by quantitatively measure the user personal preference and social influence beten users and messages to predict user's reteting behavior. Experimental results on a real-world dataset from social network show that the proposed method is effective and can improve the performance of the one-class collaborative filtering over baseline methods through leveraging ighted negative examples information."}]