  Dependency parsing (DP) is a task that analyzes text for syntactic structure
and relationship between words. DP is widely used to improve natural language
processing (NLP) applications in many languages such as English. Previous works
on DP are generally applicable to formally written languages. However, they do
not apply to informal languages such as the ones used in social networks.
Therefore, DP has to be researched and explored with such social network data.
In this paper, we explore and identify a DP model that is suitable for Thai
social network data. After that, we will identify the appropriate linguistic
unit as an input. The result showed that, the transition based model called,
improve Elkared dependency parser outperform the others at UAS of 81.42%.
