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SOPPY : A sentiment detection tool for personal online retailing

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  • 발행기관
    국제인공지능학회(구 한국인터넷방송통신학회) 바로가기
  • 간행물
    International Journal of Internet, Broadcasting and Communication KCI 등재후보 바로가기
  • 통권
    Vol.9 No.3 (2017.08)바로가기
  • 페이지
    pp.59-69
  • 저자
    Nurliyana Jaafar Sidek, Mi-Hwa Song
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A310729

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원문정보

초록

영어
The best ‘hub’ to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product’s feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.

목차

Abstract
 1. Introduction
 2. Related Works
  2.1 Literature Review
  2.2 Comparison between existing tools
  2.3 Rapid Application Development (RAD) Model
 3. SOPPY : Prototype Development
  3.1 Programming Language and Software Used in System
  3.2 System Architecture diagram
  3.3 Extraction comment from Facebook to data directory
  3.4 Pre-processing from data directory to data dictionary
  3.5 Rule-based
  3.6 System Design
 4. System Implementation
 5. Testing and Results
  5.1 Functionality testing Method
 6. Conclusion
 References

키워드

Sentiment Analysis Natural Language Processing (NLP) Semantic Role Labeling (SRL) Social Media Rapid Application Development (RAD) model

저자

  • Nurliyana Jaafar Sidek [ Data-Speaks (M) SDN BHD, Kuala Lumpur, Malaysia ]
  • Mi-Hwa Song [ Division of Information and communication technology, Semyung University, Jechon, Korea ] Corresponding author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    국제인공지능학회(구 한국인터넷방송통신학회) [The International Association for Artificial Intelligence]
  • 설립연도
    2000
  • 분야
    공학>전자/정보통신공학
  • 소개
    인터넷방송, 인터넷 TV , 방송 통신 네트워크 및 관련 분야에 대한 국내는 물론 국제적인 학술, 기술의 진흥발전에 공헌하고 지식 정보화 사회에 기여하고자 한다.

간행물

  • 간행물명
    International Journal of Internet, Broadcasting and Communication
  • 간기
    계간
  • pISSN
    2288-4920
  • eISSN
    2288-4939
  • 수록기간
    2009~2025
  • 십진분류
    KDC 326 DDC 380

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