论文标题
在社交媒体上检测对非婚姻自我伤害感兴趣的人
Detecting People Interested in Non-Suicidal Self-Injury on Social Media
论文作者
论文摘要
我们提出了一种有监督的学习方法，以检测对非自杀自伤（NSSI）感兴趣的人。我们将任务视为二进制分类问题，并根据人们自称的利益提取的功能来构建分类器。现实世界数据集（LiveJournal）社交博客网络平台上的实验评估证明了我们提出的模型的有效性。
We propose a supervised learning approach to detect people interested in Non-Suicidal Self-Injury (NSSI). We treat the task as a binary classification problem, and build classifiers based upon features extracted from people self-declared interests. Experimental evaluation on a real-world dataset, the LiveJournal social blogging networking platform, demonstrates the effectiveness of our proposed model.
