A Generative Model for Identifying Target Companies of Microblogs

Microblogging services have attracted hundreds of millions of users to publish their status, ideas and thoughts, everyday. These microblog posts have also become one of the most attractive and valuable resources for applications in different areas. The task of identifying the main targets of microblogs is an important and essential step for these applications. In this paper, to achieve this task, we propose a novel method which converts the target company identification problem to the translation process from content to targets. We introduce a topic-specific generative method to model the translation process. Topic specific trigger words are used to bridge the vocabulary gap between the words in microblogs and targets. We examine the effectiveness of our approach via datasets gathered from real world microblogs. Experimental results demonstrate a 20.2% improvement in terms of F1-score over the state-of-the-art discriminative method.