ABSTRACT
OBJECTIVES: The purpose of this study was to compare and analyse dieting practices and tendencies in 2010 and 2015 using big data. METHODS: Keywords related to diet were collected from the portal site Naver from January 1, 2010 until December 31, 2010 for 2010 data and from January 1, 2015 until December 31, 2015 for 2015 data. Collected data were analyzed by simple frequency analysis, N-gram analysis, keyword network analysis, and seasonality analysis. RESULTS: The results show that exercise had the highest frequency in simple frequency analysis in both years. However, weight reduction in 2010 and diet menu in 2015 appeared most frequently in N-gram analysis. In addition, keyword network analysis was categorized into three groups in 2010 (diet group, exercise group, and commercial weight control group) and four groups in 2015 (diet group, exercise group, commercial program for weight control group, and commercial food for weight control group). Analysis of seasonality showed that subjects' interests in diets increased steadily from February to July, although subjects were most interested in diets in July in both years. CONCLUSIONS: In this study, the number of data in 2015 steadily increased compared with 2010, and diet grouping could be further subdivided. In addition, it can be confirmed that a similar pattern appeared over a one-year cycle in 2010 and 2015. Therefore, dietary method is reflected in society, and it changes according to trends.
Subject(s)
Diet , Methods , Seasons , Weight LossABSTRACT
OBJECTIVES: The purpose of this study was to compare and analyse dieting practices and tendencies in 2010 and 2015 using big data. METHODS: Keywords related to diet were collected from the portal site Naver from January 1, 2010 until December 31, 2010 for 2010 data and from January 1, 2015 until December 31, 2015 for 2015 data. Collected data were analyzed by simple frequency analysis, N-gram analysis, keyword network analysis, and seasonality analysis. RESULTS: The results show that exercise had the highest frequency in simple frequency analysis in both years. However, weight reduction in 2010 and diet menu in 2015 appeared most frequently in N-gram analysis. In addition, keyword network analysis was categorized into three groups in 2010 (diet group, exercise group, and commercial weight control group) and four groups in 2015 (diet group, exercise group, commercial program for weight control group, and commercial food for weight control group). Analysis of seasonality showed that subjects' interests in diets increased steadily from February to July, although subjects were most interested in diets in July in both years. CONCLUSIONS: In this study, the number of data in 2015 steadily increased compared with 2010, and diet grouping could be further subdivided. In addition, it can be confirmed that a similar pattern appeared over a one-year cycle in 2010 and 2015. Therefore, dietary method is reflected in society, and it changes according to trends.
Subject(s)
Diet , Methods , Seasons , Weight LossABSTRACT
BACKGROUND: The purpose of this study is to investigate the trends on the induced abortion in Korea using social big-data and confirm whether there was time series trends and seasonal characteristics in induced abortion. METHODS: From October 1, 2007 to October 24, 2016, we used Naver's data lab query, and the search word was ‘induced abortion’ in Korean. The average trend of each year was analyzed and the seasonality was analyzed using the cosinor model. RESULTS: There was no significant changes in search volume of abortion during that period. Monthly search volume was the highest in May followed by the order of June and April. On the other hand, the lowest month was December followed by the order of January, and September. The cosinor analysis showed statistically significant seasonal variations (amplitude, 4.46; confidence interval, 1.46–7.47; p<0.0036). The search volume for induced abortion gradually increased to the lowest point at the end of November and was the highest at the end of May and declined again from June. CONCLUSION: There has been no significant changes in induced abortion for the past nine years, and seasonal changes in induced abortion have been identified. Therefore, considering the seasonality of the intervention program for the prevention of induced abortion, it will be effective to concentrate on the induced abortion from March to May.
Subject(s)
Female , Abortion, Induced , Contraception , Hand , Korea , SeasonsABSTRACT
BACKGROUND: The purpose of this study is to investigate the trends on the induced abortion in Korea using social big-data and confirm whether there was time series trends and seasonal characteristics in induced abortion. METHODS: From October 1, 2007 to October 24, 2016, we used Naver's data lab query, and the search word was ‘induced abortion’ in Korean. The average trend of each year was analyzed and the seasonality was analyzed using the cosinor model. RESULTS: There was no significant changes in search volume of abortion during that period. Monthly search volume was the highest in May followed by the order of June and April. On the other hand, the lowest month was December followed by the order of January, and September. The cosinor analysis showed statistically significant seasonal variations (amplitude, 4.46; confidence interval, 1.46–7.47; p<0.0036). The search volume for induced abortion gradually increased to the lowest point at the end of November and was the highest at the end of May and declined again from June. CONCLUSION: There has been no significant changes in induced abortion for the past nine years, and seasonal changes in induced abortion have been identified. Therefore, considering the seasonality of the intervention program for the prevention of induced abortion, it will be effective to concentrate on the induced abortion from March to May.
Subject(s)
Female , Abortion, Induced , Contraception , Hand , Korea , SeasonsABSTRACT
BACKGROUND: With the development of information and communication technology, there is a growing number of people looking for health information on the internet. This pilot study was performed to analyze the pattern of pharmacist consultation on the internet portal site. METHODS: Questions and answers posted on the portal site “Naver Jisik-iN” from March 1st to 31th in 2016 were collected. Medications asked were categorized into prescription drugs, nonprescription drugs, sanitary aids, emergency drugs, functional health foods, and others. Medications were subcategorized into 14 according to the anatomical therapeutic chemical classification system. Questions were divided into 10 categories based on Hepler's drug-related problems. RESULTS: Of the 955 cases, females accounted for 59.5% and inquirers from 11 to 40 years old, 89.4%. The number of prescription drugs, nonprescription drugs, sanitary aids, emergency drugs, functional health foods, and others were 428 (44.8%), 328 (34.3%), 31 (3.3%), 2 (0.2%), 122 (12.8%), and 44 (4.6%), respectively. Questions for drugs acting on alimentary tract and metabolism took up 27.4% followed by those on nervous system, 13.6% and anti-infectives for systemic use, 12.2%. Pharmacist consultation regarding drug information, drug interaction, and adverse reaction occupied 47.9%, 15.2%, and 12.3%, respectively. CONCLUSION: Health counseling through online is predicted to increase steadily, so pharmacists should broaden their boundaries beyond off-line pharmacies to meet social needs.