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The purpose of this study is to analyze trends of interest by big data on social networks for drone vocational training to derive key issues. The analysis tools utilized Tesxtom, Ucinet6, and NetDraw on social networks.As a result, there were issues of interest in drone acquisition, experience, training institutions and departments, practical and technical coding centers, imaging, agricultural experts, and repair as future jobs. According to the CONCOR analysis, various vocational application fields such as survey, video, racing, filming, pilot, repair, control, agriculture, elementary education, printers, practical license, consignment projects, etc.Centrality analysis showed unusual results involving the Army and the region. Teenagers are interested in the military service of Army drone disease. There were also issues of interest in the use of drones in various fields in each region by the word region and by the government and local governments and local governments. It suggests that drone-related jobs by the government and local governments may be suitable for balanced local job policies.

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º» ¿¬±¸¿¡¼­´Â ¼Ò¼È ³×Æ®¿öÅ©»ó¿¡¼­ÀÇ °í¿ë ¼­ºñ½º¿Í °ü·ÃµÈ ´ëÁß ÀÇ°ß ºò µ¥ÀÌÅ͸¦ È°¿ëÇÏ¿© ¼ö¿äÀÚµéÀÇ °ü½ÉÀ̽´¸¦ ÆľÇÇÏ´Â °ÍÀÌ ¸ñÀûÀÌ´Ù. µ¥ÀÌÅÍ´Â 2021³â 1¿ù 3ÀϺÎÅÍ 2022³â 1¿ù 3ÀÏ ±îÁö¸¦ Æ÷ÇÔÇÏ¿´´Ù. ºò µ¥ÀÌÅÍ ºÐ¼®µµ±¸´Â ÅؽºÅè(Textom)À» ±âº»À¸·Î ÇÏ¿´À¸¸ç, ¼¼ºÎÀûÀÎ ºÐ¼®À» À§ÇÏ¿© À¯¾¾³Ý(Ucinet6), ³Ý½º·Î¿ì(NetDraw) µîÀÇ ÇÁ·Î±×·¥À» È°¿ëÇÏ¿´´Ù. ±× °á°ú, ºóµµºÐ¼®°ú Àüü ³×Æ®¿öÅ©ºÐ¼®¿¡¼­´Â ¡®°í¿ë³ëµ¿ºÎ¡¯, ¡®ÀÏÀÚ¸®¡¯, ¡®º¸Ç衯, ¡®»ê¾÷¡¯, ¡®¼¾ÅÍ¡¯ µîÀÇ ´Ü¾î°¡ ÃÖ»óÀ§ ¼øÀ§ÀÇ ¼ö¿äÀÚ °ü½ÉÀ̽´·Î ³ªÅ¸³µ´Ù. °í¿ë³ëµ¿ºÎ °í¿ëº¹ÁöÇ÷¯½º¼¾ÅÍ¿¡ ¼­´Â »ê¾÷º° ÀÏÀÚ¸®¿Í º¹Áöº¸Çè¿¡ ´ëÇÑ ¿ø½ºÅé ¼­ºñ½ºÀÇ °³¼±¿¡ ´ëÇÏ¿© ÃÖ¿ì¼±ÀûÀ¸·Î ÁýÁßÇÏ´Â °ÍÀÌ ÇÊ¿äÇÏ´Ù. Á߽ɼº ºÐ¼®¿¡¼­´Â ¡®°í¿ë³ëµ¿ºÎ¡¯ ´Ü¾î°¡ ¸ðµç Á߽ɼº¿¡¼­ 1 ¼øÀ§¿¡ À§Ä¡ÇÏ°í ÀÖÀ¸¸ç, ¡®Á¤ºÎ¡¯ ´Ü¾î°¡ ÃÖ»óÀ§¿¡ Á¸ÀçÇÏ¿´´Ù. Á¤ºÎ´Â ºÎó °£, Áß¾Ó-Áö¹æ°£ Ä­¸·À̸¦ Á¦°ÅÇØ ¼ö¿äÀÚ Áß½ÉÀÇ °í¿ë0ûº¹Áö Á¾ÇÕ¼¾Å͸¦ ¿î¿µÇÏ°í ÀÖÀ¸³ª, ¼Ò¼È ³×Æ®¿öÅ©¿¡¼­´Â °í¿ë³ëµ¿ºÎÀÇ Á߽ɿªÇÒ¿¡ °ü½ÉÀÌ ÀÖ´Ù´Â °ÍÀ» ½Ã»çÇÑ´Ù. ƯÈ÷ ¸Å°³ Á߽ɼº°ú À§¼¼ Á߽ɼº¿¡¼­´Â Áö¿ªÀÇ ±â¾÷ ÀÏÀÚ¸® ä¿ëÈ®´ë¸¦ ¿¬°èÇÑ ¸ÂÃãÇü °ü¸® ¹× ¾È³», Àå·Á±Ý µîÀÇ »ç·Ê¿¡ °üÇÏ¿© ³ôÀº ºñÁßÀÇ °ü½ÉÀÌ Á¸ÀçÇÏ¿´´Ù. µû¶ó¼­ ¹Ì·¡»çȸ¿¡¼­´Â °¢ Áö¿ª ¼¾ÅÍÀÇ ¼º°ø»ç·Ê°¡ ¹ß±¼µÇ¾î °è¼ÓÀûÀ¸·Î Àû¿ëµÉ ¼ö ÀÖ´Â ¹æ¾ÈÀÌ À¯¿ëÇÒ °ÍÀÌ´Ù. CONCOR ºÐ¼®¿¡¼­´Â Áö¿ª ¼¾ÅÍÀÇ »ê¾÷º° ¾÷Á¾º° ¿ø½ºÅé ÅäÅ» Ç÷§Æû ±¸Ãà ¹× Á¶È¸, Áö¿ª Ư¼º¿¡ ¸Â´Â °í¿ë ÃËÁø, ÇýÅÃÁ¶°Ç µî¿¡ ¼Ò¼È ³×Æ®¿öÅ©ÀÇ °ü½É»ç°¡ Á¸ÀçÇÏ¿´´Ù. ¹Ì·¡»çȸ¿¡¼­´Â °¢ Áö¿ª °í¿ë ¼­ºñ½º ¼¾ÅÍÀÇ »ê¾÷ ¸ÂÃãÇü ±³À° ÈƷÿ¡ ÀÇÇÏ¿© ±â¾÷°úÀÇ Ãë¾÷ ¿¬°è¸¦ ¾Ë¼±ÇÏ´Â ½ÇõÀû ´ëÃ¥ÀÌ ÇÊ¿äÇÏ´Ù´Â °ÍÀ» ½Ã»çÇÑ´Ù.

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The purpose of this study is to analyze big data related to middle school commercial education in social network services to find out what kind of content users are interested in. For big data analysis tools, programs such as Textom, Ucinet6, and NetDraw were used.As a result, first, there was interest in administrative promotion for systematization and expansion of student service programs and entrance examination consulting. Second, There was an issue of interest in the operation of commercial education in overseas middle schools. Third, social networks were interested in government administration for various experience-related programs such as rural areas, villages, cities, and regions for each industry. In addition, they were interested in the connection of commercial education at the middle school level with industries by subject and size. There was interest in media mediums such as dot com, newsis.com, and Yonhap News about middle school commerce.These results will provide implication for the direction of education policy from the consumer¡¯s point of view such as the government-level support for middle school commercial education programs centered on job experience for each industry and corporate-linked administrative system, policy implementa- tion considering the operation of overseas middle school commercial education, career and entrance exam consulting based on commercial field experience of middle school students, and the use of commercial media etc.

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Recently, the mental strength of the Korean military has been weakened due to the slack of discipline, so measures to strengthen it are necessary. it is important to first identify and respond to the issues of interest in the military mental strength of the public. Therefore, the purpose of this study is to apply the big data related to the military mental power on numerous publics in social networks to data analysis tools such as Textom, Ucinet6, and Net Draw to issues of interest. is to derive.The results, First, as a result of analysis of frequency and centrality of key words in military mental power, the use of SNS such as blog opening and friend request appeared as a priority trend of interest. Therefore, it is necessary to devise the contents and methods of various military mental strength training using social networks. Second, the issue of military mental power interest in Israeli cases, history, and character histories was given priority in all analyses. Therefore, it is necessary to analyze the contents and methods of mental warfare used by Israel. Third, in the CONCOR analysis, relationships with life, etiquette, performance, purpose, and research were added to other analysis contents. Fourth, in the frequency analysis of key words, centrality analysis, and CONCOR analysis, changes in mental power education methods such as university special lectures by external experts, news and editorials, and reading were found to be issues of interest. Therefore, it is necessary to focus on the mental power training plan that induces active participation through special lectures or SNS that soldiers are interested in.

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¼¼°èÀûÀ¸·Î Äڷγª19 ¹ÙÀÌ·¯½º°¡ ¸¸¿¬ÇØÁü¿¡ µû¶ó ´Ù¾çÇÑ ºÐ¾ß¿¡¼­ ºñ´ë¸éÈ­¸¦ ½ÃÇàÇÏ°Ô µÇ¾ú°í, ±³À° ½Ã½ºÅÛ ¶ÇÇÑ ±Þ°ÝÇÑ ºñ´ë¸éÈ­·Î ÀÎÇØ ¸¹Àº °ü½ÉÀÌ ÁýÁߵDZ⠽ÃÀÛÇÏ¿´´Ù. º» ¿¬±¸ÀÇ ¸ñÀûÀº ÇöÀç±îÁö °è¼ÓÀûÀ¸·Î º¯È­ÇÏ°í ÀÖ´Â ±³À°È¯°æ¿¡ ¸ÂÃß¾î ºñ´ë¸é ±³À°ÀÌ ³ª¾Æ°¡¾ß ÇÏ´Â ¹æÇ⼺¿¡ ´ëÇؼ­ ºÐ¼®ÇÏ´Â °ÍÀÌ´Ù. º» ¿¬±¸¿¡¼­´Â ´Ù¾çÇÑ ÀÇ°ßµéÀÌ Á¸ÀçÇÏ´Â ¼Ò¼È³×Æ®¿öÅ© ºòµ¥ÀÌÅ͸¦ ¼öÁýÇϱâ À§ÇÏ¿© ÅؽºÅè(Textom), À¯¾¾³Ý6(Ucinet6) ºÐ¼® µµ±¸ ÇÁ·Î±×·¥À» »ç¿ëÇÏ¿© µ¥ÀÌÅ͸¦ ½Ã°¢È­ÇÏ¿´´Ù. ¿¬±¸ °á°ú 'Äڷγª'¿Í °ü·ÃµÈ Å°¿öµå°¡ ÁÖ¸¦ ÀÌ·ç¾úÀ¸¸ç '±â»ç', '´º½º'µîÀÇ ³ôÀº ºóµµÀÇ Å°¿öµåµéÀÌ Á¸ÀçÇß´Ù. ºÐ¼® °á°ú ³×Æ®¿öÅ© Àå¾Ö ¹× º¸¾È ¹®Á¦¿Í °°Àº ºñ´ë¸é ±³À°¿¡ °ü·ÃÇÑ ´Ù¾çÇÑ À̽´µéÀ» È®ÀÎÇØ º¼ ¼ö ÀÖ¾ú°í, ºÐ¼® ÀÌÈÄ ±³À° ½ÃÀåÀÇ ¼ºÀå°ú ±³À° ȯ°æÀÇ º¯È­¿¡ µû¸¥ ºñ´ë¸é ±³À° ½Ã½ºÅÛÀÇ ¹æÇ⼺¿¡ °üÇÏ¿© ¿¬±¸ÇÏ¿´´Ù. ¶ÇÇÑ ºòµ¥ÀÌÅ͸¦ ÀÌ¿ëÇÏ¿© ºÐ¼®ÇÑ ºñ´ë¸é ±³À°½ÃÀÇ º¸¾È °­È­ Çʿ伺°ú ¼ö¾÷ ¹æ½Ä¿¡ ´ëÇÑ Çǵå¹éÀÇ Çʿ伺ÀÌ Á¸ÀçÇÑ´Ù.

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¼ÒºñÀÚµéÀÇ È¯°æ¿¡ ´ëÇÑ °ü½É°ú Ã¥ÀÓ°¨ ÀÖ´Â ¼Òºñ ÇൿÀÌ ³ô¾ÆÁü¿¡ µû¶ó ÆмDZâ¾÷µéÀº Áö¼Ó°¡´É °æ¿µ È°µ¿ÀÇ Çʿ伺À» ´õ¿í ÀνÄÇÏ°Ô µÇ¾ú´Ù. º» ¿¬±¸¿¡¼­´Â SNS ºòµ¥ÀÌÅ͸¦ È°¿ëÇÏ¿© ¿¡ÄÚÆмǿ¡ ´ëÇÑ ¼ÒºñÀÚÀÇ Àνİú À̽´¸¦ Á¶»çÇÏ°íÀÚ ÇÑ´Ù. ÅؽºÆ®¸¶ÀÌ´× ±â¹ýÀ» È°¿ëÇÏ¿© 2015³â 1¿ùºÎÅÍ 2020³â 1¿ù±îÁöÀÇ ÀڷḦ ³×À̹ö, ´ÙÀ½, ±¸±Û, À¯Æ©ºê¿¡¼­ ¼öÁýÇÏ¿´´Ù. ÅؽºÅè(TEXTOM)À» ÅëÇØ ÀڷḦ ¼öÁýÇÏ°í, ºóµµºÐ¼®°ú ¸ÅÆ®¸¯½º ºÐ¼®À» ½Ç½ÃÇÏ¿´À¸¸ç, ³ëµå¿¢¼¿(NodeXL)À» »ç¿ëÇØ Å°¿öµå °£ ¿¬°á ±¸Á¶¿Í ¿¬°áÁ߽ɼº ºÐ¼®À» ÇÏ¿´´Ù. ³×Æ®¿öÅ© ½Ã°¢È­¸¦ À§ÇØ ³Ýµå·Î(NetDraw)¸¦ »ç¿ëÇÏ¿´°í, Å°¿öµåµéÀÇ ±ºÁý µµÃâÀ» À§ÇØ CONCOR ºÐ¼®À» ½Ç½ÃÇÏ¿´´Ù. ±× °á°ú, ¿¡ÄÚÆмǿ¡ ´ëÇÑ Å°¿öµå´Â ÃÑ 24,373°³°¡ ¼öÁýµÇ¾úÀ¸¸ç ÀÌ Áß ÁÖ¿ä ºóµµ¼ö¸¦ ±â¹ÝÀ¸·Î »óÀ§ 70°³ÀÇ ÁÖ¿ä Å°¿öµå¸¦ µµÃâÇÏ¿© ºÐ¼®À» ÁøÇàÇÏ¿´´Ù. ºóµµºÐ¼® °á°ú, »óÀ§ 5À§·Î ÆмÇ, ¿¡ÄÚ¹é, ºê·£µå, ´ëÇѹα¹Ä£È¯°æ´ëÀü, °¡¹æÀÌ ³ªÅ¸³µÀ¸¸ç, ¿¬°áÁ߽ɼº¿¡¼­´Â Á¦Ç°, ģȯ°æ, ÆмÇ, ¼ÒÀç, ºê·£µå°¡ °¡Àå ³ô°Ô ³ªÅ¸³µ´Ù. ¿¡ÄÚÆÐ¼Ç Ä«Å×°í¸®´Â »ê¾÷, ¾ÆÀÌÅÛ, Ä·ÆäÀÎ, ±¸¸ÅÇൿ, ±¸¸ÅÀÌÀ¯, °¨¼º¾î, ¿¡ÄÚ·Î ÃÑ 7°³·Î ³ª´©¾îÁ³À¸¸ç, À¯»ç¼ºÀÌ ÀÖ´Â Å°¿öµå¸¦ ±ºÁýÈ­ÇÑ °á°ú ¿¡ÄÚÆÐ¼Ç Á¦Ç°, Áö¼Ó°¡´ÉÇÑ »ý»ê, ±¹³»¿¡ÄÚÄ·ÆäÀÎ, ±Û·Î¹ú¿¡ÄÚÄ·ÆäÀÎÀÇ 4±×·ìÀ¸·Î ³ª´µ´Â °ÍÀ¸·Î ³ªÅ¸³µ´Ù. º» ¿¬±¸¸¦ ÅëÇØ ÆÐ¼Ç ±â¾÷ÀÇ Ä£È¯°æ ¸¶ÄÉÆà Àü·«¿¡ ´ëÇÑ ¼ÒºñÀÚµéÀÇ ÀνÄÀ» ÆľÇÇÒ ¼ö ÀÖ°í, ±â¾÷ÀÇ °í°´ Á᫐ ¸¶ÄÉÆà Àü·«¿¡ µµ¿òÀ» ÁÙ °ÍÀ¸·Î »ç·áµÈ´Ù.

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Purpose: The purpose of this study is to analyze trends in research topics related to 'new normal education.' Through this analysis, we aim to understand how 'new normal education' is perceived within the academic community, identify its limitations, and anticipate the future discussions that need to take place about 'new normal education. Method: The keywords were collected from a total of 93 academic papers and theses related to 'new normal education,' and data cleaning, frequency analysis, and co-occurrence analysis were performed using Textom. Centrality analysis and cluster analysis were conducted using Ucinet 6.758, and the results were visualized using NetDraw. Results: First, research on 'new normal education' began in 2018 and has been continuously studied until 2022, with a rapid increase in quantity in 2020-2021 due to the prolonged COVID-19 pandemic. Second, discussions in research on 'new normal education' have focused on topics such as 'online classes,' 'remote classes,' and 'non-face-to-face classes.' Rather than discussing the subjects and internal factors of education, the discussions have focused more on technology-based teaching and learning methods and external factors. Topics related to ecological education, environmental education, climate change, and community education have been hardly mentioned. Conclusion: The discourse on 'new normal education' needs to move beyond its current narrow perspective and develop a broader view that includes a reexamination of educational values and more essential discussions. Specifically, there is a need to expand quantitative and qualitative discussions on the ecological transformation of the education system, learning welfare, childcare, etc.

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ÀÌ ¿¬±¸ÀÇ ¸ñÀûÀº Å°¿öµå ³×Æ®¿öÅ© ºÐ¼®À» È°¿ëÇÏ¿© Çлý¼±¼ö °ü·Ã ±¹³» ³í¹®µéÀÇ ¿¬±¸µ¿ÇâÀ» ºÐ¼®ÇÏ´Â µ¥ ÀÖ´Ù. ÀÚ·á¼öÁýÀº ±¹³» µ¥ÀÌÅͺ£À̽º¸¦ ÀÌ¿ëÇÏ¿© 2000³âºÎÅÍ 2023³â 3¿ù±îÁö ±¹³» µîÀçÁö¿¡ °ÔÀçµÈ Çлý¼±¼ö °ü·Ã ³í¹® 912ÆíÀ» ¼öÁýÇÏ¿´´Ù. ÀÚ·á ºÐ¼®Àº ÅؽºÅè°ú À¯½Ã³ÝÀ» È°¿ëÇÏ¿© Å°¿öµå ºóµµºÐ¼®, N-gram ºÐ¼®, ³×Æ®¿öÅ© Á߽ɼº ºÐ¼®, CONCOR ºÐ¼®À» ½Ç½ÃÇÏ¿´´Ù. ¿¬±¸ °á°ú´Â ´ÙÀ½°ú °°´Ù. ù°, Àüü±â°£ Å°¿öµå ³×Æ®¿öÅ© ºÐ¼® °á°ú, °¡Àå ¸¹ÀÌ Ã⿬ÇÑ Å°¿öµå´Â Çб³¿îµ¿ºÎ, ¿îµ¿¼±¼ö, °æ±â·Â, Áø·Î, ÁöµµÀÚ·Î È®ÀεǾú´Ù. À̵é Å°¿öµå´Â Á߽ɼº ºÐ¼® °á°ú¿¡¼­µµ ¿¬°á °­µµ°¡ ³ôÀ» »Ó¸¸ ¾Æ´Ï¶ó ´Ù¸¥ Å°¿öµå »çÀÌ¿¡ À§Ä¡ÇÏ¿© ¸Å°³ ¿ªÇÒÀ» ÇÏ´Â ÁÖ¿ä Å°¿öµåÀÓÀ» ¾Ë ¼ö ÀÖ¾ú´Ù. N-gram ºÐ¼® °á°ú¸¦ ÅëÇØ Çлý¼±¼ö¿Í Çб³¿îµ¿ºÎ°¡ °áÇÕÇÏ¿© °¡Àå ¸¹ÀÌ µîÀåÇÏ´Â °ÍÀ¸·Î È®ÀεǾú´Ù. CONCOR ºÐ¼® °á°ú¿¡¼­´Â ºñ½ÁÇÑ Æ¯¼ºÀ» °¡Áø Å°¿öµå¸¦ Áß½ÉÀ¸·Î ÁöµµÀÚ, Çб³¿îµ¿ºÎ Á¤Ã¥, ¿îµ¿¼öÇà´É·Â, Áø·Î¶ó´Â ÃÑ 4°³ÀÇ ±ºÁýÀ̵µÃâµÇ¾ú´Ù. µÑ°, ½Ã±âº° Å°¿öµå ³×Æ®¿öÅ© ºÐ¼® °á°ú, Á¦1½Ã±â¸¦ Á¦¿ÜÇÏ°í Á¦2, 3, 4½Ã±â¿¡ °¡Àå ¸¹ÀÌ ÃâÇöÇÑ Å°¿öµå´Â Çб³¿îµ¿ºÎ, ¿îµ¿¼±¼ö, Áø·Î, °æ±â·Â, ÁöµµÀÚÀÓÀ» È®ÀÎÇÏ¿´´Ù. ½Ã±âº° ¿¬°á Á߽ɼºÀÇ °æ¿ì Á¦1½Ã±âºÎÅÍ Á¦4½Ã±â±îÁö Çб³¿îµ¿ºÎ¿Í ÁöµµÀÚ°¡ °¡À念Çâ·ÂÀÌ ÀÖ´Â Å°¿öµå·Î ³ªÅ¸³µÀ¸¸ç, ¸Å°³ Á߽ɼºÀÇ °æ¿ì Á¦1½Ã±â¸¦ Á¦¿ÜÇÏ°í ³ª¸ÓÁö ½Ã±â¿¡´Â Çб³¿îµ¿ºÎ¿Í °æ±â·ÂÀÌ ´Ù¸¥ Å°¿öµå»çÀÌ¿¡ À§Ä¡ÇÏ¿© Áß°³ÀÚ ¿ªÇÒÀ» ÇÏ´Â ÁÖ¿ä Å°¿öµå·Î È®ÀεǾú´Ù. º» ¿¬±¸ÀÇ °á°ú¿¡ ±Ù°ÅÇÏ¿© Çлý¼±¼ö¿Í Çб³¿îµ¿ºÎ, Çлý¼±¼ö¿Í ÁöµµÀÚ, Çлý¼±¼öÀÇ °æ±â·Â°ú Áø·Î ±³À°ÀÇ ÁÖÁ¦·Î ¿¬±¸ÀÇ ½Ã»çÁ¡À» ³íÀÇÇÏ¿´À¸¸ç, ÇâÈÄ ¿¬±¸µÇ¾î¾ß ÇÒ ÁÖÁ¦¿Í ¹æÇ⼺À» Á¦¾ðÇß´Ù.

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Given the rapid changes of fashion bags¡¯ trend phenomena, this study aims to investigate consumer perceptions of bags based on associated words with bags using SNS big data which offer immediate and diversified comments from consumers. Text mining technique was used and the text data was collected from blogs, cafe, and Facebook from search engines (Naver, Daum, Google) containing the keyword of ¡®bag¡¯ with the period from Jan 1, 2018 to Dec. 31, 2019. The frequency and matrix data of words were extracted by TEXTOM, the social matrix program. NodeXL was used to find the connection structure of words and analyze the degree centrality. The network related to bags was visualized using the NetDraw program. The CONCOR analysis was performed to make a cluster of words based on their similarities. As results, the keyword ¡®Price¡¯ showed the highest rank of frequency and degree centrality followed by ¡®Cross Bag¡¯, ¡®Good¡¯, ¡®Pretty¡¯, ¡®Backpack¡¯, ¡®Tote Bag¡¯, ¡®Travel Bag¡¯, ¡®Daily Bag¡¯, ¡®Purchase¡¯, and ¡®Boston Bag¡¯ in the top 10 frequency rankings. Results looking at highly ranked 70 keywords indicated the categories of product attributes, items, brand, and TPO. The results of CONCOR analysis demonstrated four groups including ¡®Luxury brand bag¡¯, ¡®Trend-seeking daily bag¡¯, ¡®Personal lifestyle bag¡¯, and ¡®Utility leisure bag¡¯. This study extends the scope of research by using SNS big data and provides directions for product development and marketing strategies based on customer comments and opinions.

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(Background & Purpose) This study aimed to investigate the relationship between events in public spaces and perceptions of space through big data analysis. As the subject of empirical research for this purpose, the author focused on suicide cases occurring in a public space, termed a ¡°bridge.¡± The high suicide rate in Korea is one of the oldest social problems. Suicide-related research so far has been focused on individuals' private spaces or psychological factors, and suicide research targeting public spaces is insufficient. In this study, text data on the Han River, a location where suicides frequently occur, were collected, and text mining analysis was conducted. The reason for doing so is to suggest the direction of public design to cope with suicide in public places in the future by examining how events taking place in space are recognized. (Method) Through literature research, the concepts of traditional space and event as attributes that define space were considered. The relationship between events and language was explored, and the current status of suicide in public places was introduced. For empirical analysis, text mining was conducted by collecting and refining unstructured data from Naver and Daum blogs, news, cafes, and intellectuals. Keyword frequency analysis, TF-IDF, network analysis, and cluster analysis were all performed and visualized using the big data analysis programs Textom and Ucinet. (Results) Keywords related to suicide prevention (e.g., bridge, suicide, installation, safety) appeared frequently. As a result of the TF-IDF analysis, keywords such as Han River Bridge, jumping suicide, and extremes rose in ranking. In other words, the perception of the event itself was treated with great importance. Installation-related keywords showed a high frequency in both the frequency analysis and TF-IDF analysis, confirming that they were mainly mentioned when an incident of installing something in a space occurred. The eight groups shown in the cluster analysis could be classified into physical, human, and temporal factors; however, the cognitive factors were insufficient. (Conclusions) Suicide in public places is complex and cannot be understood or resolved using a single cause or method. Awareness of suicide on bridges was concentrated on the installation of suicide prevention structures, operation of a helpline, and rescue activities, and cultural attempts to change perceptions were found to be insignificant. To change the perception of space in the future, events occurring in space should be further expanded in facility installation or rescue activities, and spatial design should be carried out at a cultural level to improve the negative image or the public space perception.

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(Background and Purpose) As the times change, various methods to solve social problems are underway around the world. In order to solve problems in the public domain such as human rights as well as the environment, various topics were presented in the international community and activities were started. Since there is a limit to simply implementing it in state agencies to solve public problems, various collaborations with the private sector are required. The purpose of this study is to interpret various changes in our society for the expansion of public design, understand the meaning relationship of the results, and make basic data to set the direction for future expansion. (Method) Through literature research, we examine how cooperative projects led by the private sector are related to public design. Through this, detailed keywords are derived and the contents of public projects implemented in the private sector are analyzed. For empirical analysis, text mining is conducted on various elements of projects executed for the public sector in the private sector using big data on the Internet. The method of collecting and refining unstructured data distributed on the portal platform is applied. For the analysis of the derived big data, keyword frequency analysis, TF-IDF, network analysis, and cluster analysis are performed and visualized using analysis tools of Textom and Ucinet. (Results) The top 100 related keywords were extracted through frequency analysis, and keywords centered on companies and public designs such as management, corporate, public design, society, and design were derived as the main keywords. Through TF-IDF analysis, it was confirmed that the keywords of management, company, and public design were located at the top, and the contents of public design were related to corporate management activities. Through cluster analysis, it was confirmed that corporate management activities were expanding to various methods, and through keywords such as public design, society, and management, public design was applied to apply elements of management to society. (Conclusions) Activities implemented in the private sector and in the public sector lead to activities consistent with the value of public design. It was possible to derive the results of the expansion of corporate activities for the purpose of improving publicity rather than implementing projects in the public domain only to pursue profits. In addition, it was confirmed that public design can be used as a method of projects implemented in the private sector through the results derived from society, environment, sharing, social contribution, and practice. The possibility of applying the study was confirmed by expanding the published linguistic data, and the possibility of future expansion of public design was confirmed through the derived results.

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