• Title/Summary/Keyword: Crawling

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A Web application vulnerability scoring framework by categorizing vulnerabilities according to privilege acquisition (취약점의 권한 획득 정도에 따른 웹 애플리케이션 취약성 수치화 프레임워크)

  • Cho, Sung-Young;Yoo, Su-Yeon;Jeon, Sang-Hun;Lim, Chae-Ho;Kim, Se-Hun
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.22 no.3
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    • pp.601-613
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    • 2012
  • It is required to design and implement secure web applications to provide safe web services. For this reason, there are several scoring frameworks to measure vulnerabilities in web applications. However, these frameworks do not classify according to seriousness of vulnerability because these frameworks simply accumulate score of individual factors in a vulnerability. We rate and score vulnerabilities according to probability of privilege acquisition so that we can prioritize vulnerabilities found in web applications. Also, our proposed framework provides a method to score all web applications provided by an organization so that which web applications is the worst secure and should be treated first. Our scoring framework is applied to the data which lists vulnerabilities in web applications found by a web scanner based on crawling, and we show the importance of categorizing vulnerabilities according to privilege acquisition.

Does Rain Really Cause Toothache? Statistical Analysis Based on Google Trends

  • Jeon, Se-Jeong
    • Journal of dental hygiene science
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    • v.21 no.2
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    • pp.104-110
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    • 2021
  • Background: Regardless of countries, the myth that rain makes the body ache has been worded in various forms, and a number of studies have been reported to investigate this. However, these studies, which depended on the patient's experience or memory, had obvious limitations. Google Trends is a big data analysis service based on search terms and viewing videos provided by Google LLC, and attempts to use it in various fields are continuing. In this study, we endeavored to introduce the 'value as a research tool' of the Google Trends, that has emerged along with technological advancements, through research on 'whether toothaches really occur frequently on rainy days'. Methods: Keywords were selected as objectively as possible by applying web crawling and text mining techniques, and the keyword "bi" meaning rain in Korean was added to verify the reliability of Google Trends data. The correlation was statistically analyzed using precipitation and temperature data provided by the Korea Meteorological Agency and daily search volume data provided by Google Trends. Results: Keywords "chi-gwa", "chi-tong", and "chung-chi" were selected, which in Korean mean 'dental clinic', 'toothache', and 'tooth decay' respectively. A significant correlation was found between the amount of precipitation and the search volume of tooth decay. No correlation was found between precipitation and other keywords or other combinations. It was natural that a very significant correlation was found between the amount of precipitation, temperature, and the search volume of "bi". Conclusion: Rain seems to actually be a cause of toothache, and if objective keyword selection is premised, Google Trends is considered to be very useful as a research tool in the future.

COVID-19 and Korean Family Life on Social Media: A Topic Model Approach (소셜 빅데이터로 알아본 코로나19와 가족생활: 토픽모델 접근)

  • Park, Sunyoung;Lee, Jaerim
    • The Journal of the Korea Contents Association
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    • v.21 no.3
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    • pp.282-300
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    • 2021
  • The purpose of this study was to explore what social media posts tell us about family life during the COVID-19 pandemic by examining the keywords and topics underlying posts on blogs and online forums. Our criteria for web crawling were (a) blog and forum posts on Naver and Daum, the top portal sites in Korea, (b) posts between February 23 and April 19, 2020, the period of the first heightened social distancing orders, and (c) inclusion of "COVID" and "family" or "COVID" and "home." We analyzed 351,734 posts using TF-IDF values and topic modeling based on latent Dirichlet allocation. We identified and named 22 topics including COVID-19 prevention, family infection, family health, dietary life and changes, religious life, stuck at home, postponed school year, family events, travel and vacations, concerns about family and friends, anxiety and stress, disaster and damage, COVID-19 warning text messages, family support policies, Shin-cheon-ji and Daegu. The results show that COVID-19 impacted various domains of family life including health, food, housing, religion, child care, education, rituals, and leisure as well as relationships and emotions.

Analysis for Daily Food Delivery & Consumption Trends in the Post-Covid-19 Era through Big Data

  • Jeong, Chan-u;Moon, Yoo-Jin;Hwang, Young-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.231-238
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    • 2021
  • In this paper, we suggest a method of analysis for daily food delivery & consumption trends through big data of the post-Covid-19 era. Through analysis of big data and the database system, four analyzed factors, excluding weather, was proved to have significant correlation with delivery sales for 'Baedarui Minjok' of a catering delivery application. The research found that KBS, MBC and SBS Media showed remarkable results in food delivery & consumption sales soaring up to about 60 percent increase on the day after the Covid-19 related new article was issued. In addition, it proved that mobile media and web surfing were the main factors in increasing sales of food delivery & consumption applications, suggesting that viral marketing and emotional analysis by crawling data from SNS used by Millennials might be an important factor in sales growth. It can contribute the companies in the economic recession era to survive by providing the method for analyzing the big data and increasing their sales.

The Effect of Discomfort Index on Outfielder's Game Record Data (불쾌지수가 외야수의 경기 기록 데이터에 미치는 영향)

  • Kim, Semin;Shin, Chwa-Cheol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.8
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    • pp.978-984
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    • 2020
  • In this study, the correlation between sports records and weather data was analyzed using the big data analysis method. To this end, data was collected by API and crawling, data was processed, statistics were performed, and data visualization was performed. The subject of this study was a player who entered the regular at-bat among outfielders in the 2019 KBO League. In addition, meteorological data were analyzed by using the unpleasant index and above 70 and below 70. As a result of the study, in the various hitting indicators, which are the records that pitchers intervene, the higher the unpleasant index, the better the outfielder's record, but pitchers, walks, pitches, pitching success rates, pitches per turn, pitches per game From the records of the back, it was found that the outfielder made the pitcher difficult. It is expected that this study will help the development of the sports data industry and the performance of baseball players, baseball teams, and coaching staff.

Analysis of Research Trends in Elementary Information Education According to Changes in Curriculum (교육과정 변화에 따른 초등 정보교육 연구 동향 분석)

  • Lee, Youngho
    • Journal of The Korean Association of Information Education
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    • v.25 no.3
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    • pp.537-545
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    • 2021
  • Contents related to computers in the curriculum have been presented from the 5th curriculum released in 1987. The practical education curriculum of the 2015 revised curriculum is composed of software-related content from the existing ICT-related contents. Related research needs to be preceded in order to revise the curriculum according to the times and social needs. Research on elementary school information education is mainly conducted by the Korean Society for Information Education. Therefore, in this study, based on the thesis of the Society for Information Education, the research trends of the society were analyzed by a period of change in the curriculum. Research Results The research of the society shows a change in research trends similar to the change in the curriculum. And it can be seen that the research of society precedes the change in the curriculum.

Determinants of Wage for Web-based Platform Workers: In perspective of evaluation by previous employers (웹 기반형(Web-based) 플랫폼 노동자의 임금 결정요인: 이전 고용주에 의한 평가의 관점에서)

  • Lim, Jisun
    • Journal of Digital Convergence
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    • v.20 no.4
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    • pp.1-14
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    • 2022
  • The purpose of this study was to find the wage determinants of web-based platform workers. For this purpose, a total of 3,575 web-based platform workers' information from Freelancer.com, a global platform labor market, in September 2018 were used and whether or not newly available indicators such as evaluations by previous employers had a significant effect on the wage increase of platform workers using OLS and QR methods. As an OLS estimation results, the number of reviews, as well as education and experience, affects the wages of platform workers. However, as a result of the QR estimation, experience rather than education, recommendation rather than a review has a more significant effect on the wage of web-based platform workers as the wage level rises.

Is BTS Different? Shared Episodes on SNS as a Good Indicator for Celebrity Endorsed Ad Effects

  • Bu, Kyunghee;Kim, Whoe Whun
    • Asia Marketing Journal
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    • v.22 no.4
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    • pp.27-45
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    • 2021
  • This study examines the effects of celebrity endorsed advertising from a new perspective of the prior research that emphasizes the matchup between the brand and the celebrity. Due to the recent sharing experiences of the celebrity and their fans on SNS, it is hypothesized that the shared stories would impact viewers' responses that are often expressed in their likes, dislikes, shares and comments on SNS. In this study, the episodic type of advertising is hypothesized to have more favorable and active responses from viewers than the typical celebrity image-focused ads would have. By crawling and analyzing viewers' responses on YouTube toward 12 BTS endorsed ads, the hypotheses are confirmed as higher ratio of likes, lower ratio of dislikes and significantly higher ratio of comments over both total views and total likes were found. For the rationale behind, total 1800 comments were categorized into 4 major content types such as attached, experiential, empathic and self-related ones that are all considered as important factors influencing the strong ad effect. The results showed that the episodic ads have marginally more emotional comments than the celeb image ads. The difference was only found in experiential and empathic responses but not in self-related responses. Contrary to the hypothesis, the comments expressing attachment were found more for the celebrity image-focused ads than the episodic ones. It does not seem to suggest that the celebrity image focused ads are better to capture viewers' attachment towards the celebrity and the ad endorsed, but that the episodic ads draw viewers into relatively deeper level of attachment such as empathy by perceiving the authenticity of the celebrity and the brand. In conclusion, the shared stories on SNS can be a factor in the match-up theory on celebrity endorsed ad effects.

Text Data Analysis Model Based on Web Application (웹 애플리케이션 기반의 텍스트 데이터 분석 모델)

  • Jin, Go-Whan
    • The Journal of the Korea Contents Association
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    • v.21 no.11
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    • pp.785-792
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    • 2021
  • Since the Fourth Industrial Revolution, various changes have occurred in society as a whole due to advance in technologies such as artificial intelligence and big data. The amount of data that can be collect in the process of applying important technologies tends to increase rapidly. Especially in academia, existing generated literature data is analyzed in order to grasp research trends, and analysis of these literature organizes the research flow and organizes some research methodologies and themes, or by grasping the subjects that are currently being talked about in academia, we are making a lot of contributions to setting the direction of future research. However, it is difficult to access whether data collection is necessary for the analysis of document data without the expertise of ordinary programs. In this paper, propose a text mining-based topic modeling Web application model. Even if you lack specialized knowledge about data analysis methods through the proposed model, you can perform various tasks such as collecting, storing, and text-analyzing research papers, and researchers can analyze previous research and research trends. It is expect that the time and effort required for data analysis can be reduce order to understand.

Network Analysis of Keywords Related to Korean Nurse: Focusing on YouTube Video Titles (국내 간호사 관련 동영상 키워드의 네트워크 분석: 유튜브 동영상 제목을 중심으로)

  • Lee, Dongkyun;Lee, Youngjin;Lee, Bogyeong;Kim, Sujin;Park, Haejin;Bae, Sun Hyoung
    • Journal of Home Health Care Nursing
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    • v.29 no.3
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    • pp.278-287
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    • 2022
  • Purpose: To analyze Korean nurse-related channels and video titles on YouTube, the world's largest online video sharing and social media platform, to clarify public opinion and image of nurses. We seek utilization strategies and measures through current status analysis. Methods: Data is collected by crawling video information related to Korean nurses, and correlation is analyzed with frequent word analysis and keyword network analysis. Results: Through the YouTube algorithm, 2,273 videos of 'Nurse' were analyzed in order of recent views, relevance, and rating, and 2,912 videos searched for with the keyword 'Nurse + Hospital, COVID-19, Awareness, University, National Examination' were analyzed. Numerous videos were uploaded, and nursing work that was uploaded in the form of a vlog recorded a high number of views. Conclusion: We could see if the YouTube video shows images of nurses. It has been confirmed that various information is being exchanged rather than information just for promotional purposes.