Abstract:

Network Informal Language Expression (NILE) has the characteristics of novelty, unconventionality and colloquialism,which poses a challenge to many natural language processing tasks. In the process of using online language for communication, some NILEs are gradually standardized and normalized, forming a crucial part of the NILE terminology. By collecting, processing and analyzing more than 460 000 tweets, we divide English NILEs into 13 categories from the perspectives of sound, form and sense, and further analyzed their characteristics. Taking the advantage of statistic-based approach and rule-based approach, we design an automatic English NILE recognition system based on the integration of statistical techniques and linguistic rules, and thereupon build a terminology database of 7000 NILE items.

Key words: Network Informal Language Expression (NILE), automatic recognition, terminology database