• Title/Summary/Keyword: 버즈 모니터링

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A Study on the Case Analysis of Customer Reputation based on Big Data (빅 데이터를 이용한 고객평판 사례분석에 관한 연구)

  • Song, Eun-Jee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.10
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    • pp.2439-2446
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    • 2013
  • Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Since development of IT has created massive information, social big data extremely increased. Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Because social big data plays an important role for getting customer feedback, a lot of corporations are interested in analyzing and applying of social big data. Collecting and analyzing social big data is operated by Buzz monitoring system. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents examples of customer reputation using buzz monitoring. In the paper, after all, it would analyze the result from the customer reputation, and research the implication.

A Study on Hotel Customer Reputation Analysis based on Big Data (빅 데이터 기반 호텔고객 평판 분석에 관한 연구)

  • Kong, Hyo-Soon;Song, Eun-Jee
    • Journal of Digital Contents Society
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    • v.15 no.2
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    • pp.219-225
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    • 2014
  • Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Social media like Twitter and Facebook let customers to express their needs, and using big data such as data on SNS is a very effective method for getting customer's feedback. Collecting and analyzing social big data are operated by Buzz monitoring system. This research suggests how to utilize big data for getting customer's feedback on hotel CRM(Customer Relationship Management), which considers customer itself as asset of business. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents results of hotel customer reputation using buzz monitoring system. It would analyze the result from the hotel customer reputation, and research the implication in this paper.

A Study on the Comparison Analysis of Travel Agencies using Social Big Data (소셜 빅 데이터를 이용한 여행사 비교 분석에 관한 연구)

  • Song, Eun-Jee;Kong, Hyou-Soon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.771-772
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    • 2015
  • 소셜미디어 상 고객들이 쏟아내는 말을 실시간으로 분석, 조사하는 방법으로 버즈 모니터링 이라는 시스템을 이용하여 웹상의 다양한 정보를 자동으로 검색하고 수집하고 있다. 본 논문에서는 여행사에 관해 소셜 미디어 상의 빅 데이터를 이용하여 보다 정확하고 효율적인 정보 수집과 분석이 가능하도록 하기위한 분석 모델을 제안하고 실제 국내 여행사에 관해 비교 분석한다. 먼저 여행사별 인지도,이미지와 선호도 분석을 하고 관광관련 상품과 서비스에 대한 분석과 함께 소비자 분석으로서 관광의 목적, 동행인 등 소비자의 생활패턴에 대한 분석을 한다. 또한 여행사 관련 영향력자 경향을 트위터 상에서 살펴본 결과 해당 여행사 이용경험자와 관련 뉴스를 제공하는 언론, 이벤트에 관심 있는 사용자들로 유형화 할 수 있었다.

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A Study on the Evaluation of Travel Agency using Social Big Data (소셜 빅 데이터를 이용한 여행사 평가에 관한 연구)

  • Kong, Hyo-Soon;Song, Eun-Jee;Kang, Min-Shik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.10
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    • pp.2241-2246
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    • 2015
  • Recently for efficient management, companies have collected and investigated information about customers' feedback by using a system that analyzes big data from social media. This paper proposes more accurate and efficient evaluation method of collecting and investigating customers' feedback using social big data for travel agency, which is representative company of hospitality industry. First, it designs service model and, as a test-bed, analyzes media channel, customer satisfaction, and brand-image etc. of big 5 travel agencies in Korea. In addition, we suggest an analysis result of evaluating preference with positive rate and negative rate by proposed evaluation method. It allows a travel agency to know which area should be improved corresponding to evaluation item; thus, suggested evaluation method is effective to manage customers even more efficiently.