The study of ontology model for soccer player's social media contents analysis

Abstract

Purpose Soccer-related social media BigData includes complex information related to soccer players and is continuously and instantly generated. Text mining research is actively carried out for this kind of social media contents analysis, but it tends to be analyzed with limited linguistic characteristics such as understanding of language complexity and context, ambiguous terms, rhetoric, and new terms. This can be attributed to the fact that the tools commonly used for text mining use universal terminology dictionaries and packages that exclude the peculiarities of the analysis themes. The purpose of this study is to develop an Ontology model, which are representative tools for defining semantic ambiguity and relationships and systems between terms of text data. Methods In order to achieve the research objectives, we applied the 7-step development method of ‘Ontology Development 101: A Guide to Creating Your First Ontology’, which is useful for ontology development. Each step includes 1) Determine the domain and scope of the ontology 2) Consider reusing existing ontology 3) Enumerate important terms in the ontology 4) Define the classes and the class hierarchy 5) Define the properties of classes-slots 6) Define the facts of the slots 7) Create instances. In particular, the 3rd-step of this study, the glossary stage, is to extract core terms that make up he ontology, but since the goal of this study is to develop the ontology that can be used in social media contents analysis of soccer players, we conducted a social media text analysis related to actual soccer players and selected 484 core terms. Results The ontology which was developed in this research for social media contents analysis of soccer players consisted largely of four parts(General terms, performance results terms, common terms, and Characteristic term) and classified according to the content characteristics of the term. Conclusion Developed ontology in this study is object-oriented that defining classes and objects to define divisions and relationships between terms and also means a social media contents knowledge system of soccer players. In addition, it performs a function as a secondary tool which can be utilized for atypical data analysis.

Keywords

• ontology
• bigdata
• text mining
• object orientation
• social media