• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.21-24
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• 2018

기존 Facebook 페이지의 경우에는 수많은 제보 글이 올라와 사용자가 원하는 글을 찾기 어렵다는 문제점이 발생하고 있다. 본 논문에서는 이를 위해 다양한 Facebook 페이지 내용을 크롤링하여 사용자가 원하는 Facebook 페이지 내용을 검색하여 사용자에게 제공할 수 있도록 데이터베이스 서버에 저장 한 후 크롤링 된 Facebook 페이지 내용을 제공할 수 있는 웹사이트를 설계하고 구현한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.467-468
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• 2021

본 논문에서는 자료수집(데이터 크롤링)을 이용해 많은 채용정보를 쉽게 접근할 수 있도록 하는 시스템이다. 현재는 StackOverflow의 자료를 수집하고 데이터베이스에 자동으로 저장하도록 하였다. 수집해야 할 자료가 많아 Celery와 RabbitMQ를 사용하여 비동기 작업을 요청하여 즉시 응답을 받지 않아도 다른 일을 수행할 수 있다. 이렇게 수집한 자료들을 해당 사이트에 나열해줌으로 사용자들이 시간과 비용을 절감하여 효율적인 취업 준비를 할 수 있도록 하는 시스템을 설계 구현하였다.

• Journal of Multimedia Information System
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• v.2 no.3
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• pp.287-294
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• 2015

We are living in epoch of information when Internet touches all aspects of our lives. Therefore, it provides a plenty of services each of which benefits people in different ways. Electronic Mail (E-mail), File Transfer Protocol (FTP), Voice/Video Communication, Search Engines are bright examples of Internet services. Between them Social Network Services (SNS) continuously gain its popularity over the past years. Most popular SNSs like Facebook, Weibo and Twitter generate millions of data every minute. Twitter is one of SNS which allows its users post short instant messages. They, 100 million, posted 340 million tweets per day (2012)[1]. Often big amount of data contains lots of noisy data which can be defined as uninteresting and unclassifiable data. However, researchers can take advantage of such huge information in order to analyze and extract meaningful and interesting features. The way to collect SNS data as well as tweets is handled by crawlers. Twitter crawler has recently emerged as a great tool to crawl Twitter data as well as tweets. In this project, we develop Twitter Crawler system which enables us to extract Twitter data. We implemented our system in Java language along with MySQL. We use Twitter4J which is a java library for communicating with Twitter API. The application, first, connects to Twitter API, then retrieves tweets, and stores them into database. We also develop crawling strategies to efficiently extract tweets in terms of time and amount.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.219-224
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• 2022

The Korea Meteorological Administration(KMA) has been released life-related indexes such as 'Life industrial weather information' and 'Safety weather information' while other countries' meteorological administrations have been made 'Human-biometeorology' and 'Health meteorology' indexes that concern human sensibility effections to diverse criteria. Although human sensibility changes have been studied in psychological research criteria with diverse and innumerous application areas, there are not enough studies that make data mining based validation of sensibility change factors. In this research I made models to estimate sensibility change caused by weather factors such as temperature and humidity, and validated by collecting sensibility data from SNS text crawling and weather data from KMA public dataset. By Logistic Regression, I clarify factors affecting sensibility changes.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.241-244
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• 2017

인터넷을 이용하는 사용자들은 원하는 정보를 획득하고 타인들과 소통하기 위한 방법으로 소셜 네트워크 서비스를 이용한다. SNS는 사용자별로 차별화된 기능을 제공함으로써 수요자를 증가시키지만 이를 활용하는 사용자들은 무분별한 콘텐츠를 접함으로써 사용자 인터페이스에 대한 불편함은 더해가고 있다. 본 연구는 SNS를 이용하는 사용자들의 사용자 편이성을 증가하고 콘텐츠 접근성을 강화하는 방안으로 원하는 관심사만 자동으로 수집하여 열람하도록 JAVA WEB CRAWLING을 활용하여 시스템을 개발하였다.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.195-200
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• 2019

Nowadays as the use of mobile communication devices such as smart phones and tablets and the use of Computer is expanded, data is being collected exponentially on the Internet. In addition, due to the development of SNS, users can freely communicate with each other and share information in various fields, so various opinions are accumulated in the from of big data. Accordingly, big data analysis techniques are being used to find out the difference between the response of the general public and the response of the media. In this paper, we analyzed the public response in SNS about child allowance and childbirth grant and analyzed the response of the media. Therefore we gathered articles and comments of users which were posted on Twitter for a certain period of time and crawling the news articles and applied sentiment analysis. From these data, we compared the opinion of the public posted on SNS with the response of the media expressed in news articles. As a result, we found that there is a different response to some national policy between the public and the media.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.655-665
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• 2018

Social network services (SNS) have become the most common tool for the communication of public and private opinions as well as public issues; consequently, one may form or drive public opinions to advocate by spreading positive content using SNS. Controversy for survey data based opinion poll accuracy continues in relation to response rate or sampling methodology. This study suggests complementary measures that additionally consider the sentiment analysis results of unstructured data on a social network by data crawling and sentiment dictionary adjustment process. The suggested method shows the improvement of prediction accuracy by decreasing error rates.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.169-170
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• 2017

In this paper, we analyze contents of formal and non - standardized data to understand what factors affect the ratings of drama. The formalized data collection collected 19 items from the four areas of drama information, person information, broadcasting information, and audience rating information of each broadcasting company. In order to collect unstructured data, crawling techniques were used to collect bulletin boards, pre - broadcast blogs and post - broadcast blogs for each drama. From the collected data, it was found that the differences according to broadcasting time, the start time, genre, and day of broadcasting were similar among broadcasting companies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.438-440
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• 2014

Recently it is used commercially to actively move the data from the SNS service. Therefore, we propose a method that can accurately analyze the information related to the reputation of companies and products in real time SNS environment in this paper.Identify the relationship between words by performing morphological analysis on the text data gathered by crawling the SNS scheme. In addition, it shows the visualization to analyze statistically through a established emotional dictionary morphemes are extracted from the sentence. Here, if the extracted word is not exist in sentimental dictionary. Also, we propose the algorithm that add the word to emotional dictionary automatically.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.399-401
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• 2016

제안된 시스템은 다양한 소셜 네트워크에서 사용자가 입력한 키워드를 기반으로 데이터를 수집하여 형태소 분석을 거쳐 사용자에게 통계정보 및 키워드에 대한 오피니언 마이닝 결과를 제공한다. SNS 상에 수많은 정보들이 저장되는데, 이를 이용하는 과정에서 단편적인 정보밖에 얻을 수 없는 비전문적인 사용자에게 유용한 데이터를 제공하기 위해 Opinion Mining 및 다양한 통계적 분석을 통해 키워드에 대한 시각화 정보를 출력한다.