Who Will You "@"?

Yeyun Gong, Qi Zhang, Xuyang Sun, Xuanjing Huang

Abstract: In Twitter-like social networking services, people can use the "@" symbol to mention other users in tweets and send them a message or link to their profiles. In recent years, social media services are rapidly growing with thousands of millions of users participating in them every day. When the "@" symbol is entered, there should be an automatic suggestion function which recommends a small list of candidates in order to help users to easily identify and input usernames. In this paper, we present our work on building a recommendation system for the mention function in microblogging services. The recommendation strategy we used takes into consideration not only content of the microblog but also histories of candidate users. To better handle these textual information, we propose a novel method that extends the translation-based model. Experimental results on the dataset we collected from a real world microblogging service demonstrate that the proposed method outperforms state-of-the-art approaches.