The Semantic Analysis of Twitter Data with Generative Lexicon for the Information of Traffic Congestion

Abstract

This research is closely related to the semantic analysis of Twitter Data with Generative Lexicon for getting information of traffic congestion. This research aims to generate the semantic analysis with Generative Lexicon to obtain structured information about traffic congestion conditions. Semantic analysis is conducted through several stages, namely data acquisition, text segmentation, detection of types and meanings of the words, and (4) semantic analysis. The results of this research, the system can determine the congestion conditions based on the semantic analysis. The system also separates the data of place and time of occurrence of tweets on Twitter.