Keyword extraction for social snippets

Today, a huge amount of text is being generated for social purposes on social networking services on the Web. Unlike traditional documents, such text is usually extremely short and tends to be informal. Analysis of such text benefit many applications such as advertising, search, and content filtering. In this work, we study one traditional text mining task on such new form of text, that is extraction of meaningful keywords. We propose several intuitive yet useful features and experiment with various classification models. Evaluation is conducted on Facebook data. Performances of various features and models are reported and compared. Categories and Subject Descriptors: H.3.1 [Content Analysis xing]: Abstracting methods, H.4.m [Information Systems]: Miscellaneous. General Terms: Algorithms, Experimentation, Performance.

• Type: Conference
• Year: 2010
• Where: WWW
• Authors: Zhenhui Li, Ding Zhou, Yun-Fang Juan, Jiawei Han
• Keywords: Internet Technology, Social Networking Services, Text Mining Task, Various Classification Models, WWW 2010