Participant Selection for Information Diffusion Based on Topic and Emotion Preference Learning

The rapid development of social networks has woven themselves into people's daily life and become indispensable platforms with superior commercial and scientific values. Both companies and governments have discovered the potential effectiveness of employing social network users for information diffusion. Rather than only selecting a group of users who are interested in target topic, it is more beneficial to choose users with desired emotion preference to help diffuse information under certain emotional expectation. In this paper, we propose an emotional participant selection system that not only considers user's topic preference, but also more importantly takes user's emotional influence into account. Specifically, a dynamic forgetting mechanism is applied to learn user's topic preference, and independent cascade model is leveraged to construct emotional influence. Combining these two features, we develop an algorithm that can accomplish the task for emotional participant selection. Experimental results on a real-world data set validate the effectiveness of our proposed method.