Goal-Setting and “Meaning-Making” in Mined Dataset of Tweets Using SFG Approach  

作　　者：Jie Shi Sébastien Louvigné 

机构地区：[1]Division of Social Sciences, Graduate School of Informatics and Engineering, The University of Electro-Communications, Chofu 182-8585, Japan [2]Information Processing Laboratory, Graduate School of Information Systems, The University of Electro-Communications, Chofu 182-8585, Japan

出　　处：《Journal of Electrical Engineering》2014年第1期20-28,共9页电气工程（英文版）

摘　　要：Goal-setting enhances learning by providing a sense of direction and purpose to individuals. Contemporary social media plays an important role in expressing individual users＇ messages and sharing personal goals within a given community. The massiveness of the data available for users calls for a more systematic analysis of goals and meaning-making construction of these goals for educational and research purposes. This research proposes an approach to combine methods of mining, corpus linguistics and SFG （systemic functional grammar） for extracting goals in mined tweets, sorting the data linguistically and devising a model for analyzing the data based on the concepts of SFG and genre-based realization. The results of ＂meaning-making＂ analysis of goals show that： （1） mining is a successful tool for processing the large database into the pre-designated typology of goals; （2） the implementation of SFG as an analytical theory for semiotic and semogenic features of goals is a significant expansion of linguistic analysis of goals; （3） the Transitivity Model of SFG for identifying the Ideational Function of social meaning creation shows thc inclination of using ＂material＂, ＂mental＂ and ＂relational＂ processes as well as personal recounts of past learning experiences.

关 键 词：GOAL-SETTING observational learning data mining SFG SEMIOTICS 

分 类 号：TM93[电气工程—电力电子与电力传动]