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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö > Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö ¼ÒÇÁÆ®¿þ¾î ¹× µ¥ÀÌÅÍ °øÇÐ

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Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) 꺿 µ¥ÀÌÅÍ¿¡ ³ªÅ¸³­ ¿ì¿ï ´ã·ÐÀÇ ¹üÁÖ¿Í Æ¯¼ºÀÇ ÀÌÇØ
¿µ¹®Á¦¸ñ(English Title) Understanding the Categories and Characteristics of Depressive Moods in Chatbot Data
ÀúÀÚ(Author) HyoJin Chin   Chani Jung   Gumhee Baek   Chiyoung Cha   Jeonghoi Choi   Meeyoung Cha   ÁøÈ¿Áø   Á¤ÂùÀÌ   ¹é±ÝÈñ   Â÷Áö¿µ   ÃÖÁ¤È¸   Â÷¹Ì¿µ  
¿ø¹®¼ö·Ïó(Citation) VOL 11 NO. 09 PP. 0381 ~ 0390 (2022. 09)
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(Korean Abstract)
ÀÚ¿¬¾îó¸® ±â¼ú°ú ºñ´ë¸é ¹®È­ÀÇ È®»ê°ú ´õºÒ¾î 꺿ÀÇ »ç¿ë Áõ°¡¼¼°¡ °¡Æĸ£¸ç, 꺿ÀÇ ¿ëµµ ¶ÇÇÑ ÀÏ»ó ´ëÈ­¿Í ¼ÒºñÀÚ ÀÀ´ë¸¦ ³Ñ¾î¼­ Á¤½Å °Ç°­À» À§ÇÑ ¿ëµµ·Î È®ÀåÇÏ°í ÀÖ´Ù. 꺿Àº ÀÍ¸í¼ºÀÌ º¸ÀåµÈ´Ù´Â Á¡¿¡¼­ »ç¿ëÀÚµéÀÌ ¿ì¿ï°¨¿¡ °üÇØ À̾߱âÇϱâ ÀûÇÕÇÑ ¼­ºñ½ºÀÌ´Ù. ±×·¯³ª »ç¿ëÀÚ°¡ ÀÛ¼ºÇÑ ¹®ÀåµéÀ» ºÐ¼®ÇØ ¿ì¿ï ´ã·ÐÀÇ À¯Çü°ú Ư¼ºÀ» ÆľÇÇÏ´Â ¿¬±¸µéÀº ÁÖ·Î ¼Ò¼È ³×Æ®¿öÅ© µ¥ÀÌÅ͸¦ ´ë»óÀ¸·Î Çß´Ù´Â ÇÑ°èÁ¡ÀÌ Á¸ÀçÇϸç, ½ÇÁ¦ ȯ°æ¿¡¼­ »ç¿ëµÇ´Â 꺿°ú »óÈ£ÀÛ¿ëÇÑ µ¥ÀÌÅ͸¦ ºÐ¼®ÇÑ ¿¬±¸´Â ã¾Æº¸±â Èûµé´Ù. ÀÌ ¿¬±¸¿¡¼­´Â 꺿-»ç¶÷ÀÇ »óÈ£ÀÛ¿ë µ¥ÀÌÅÍ¿¡¼­ ¹«ÀÛÀ§·Î ÃßÃâÇÑ ¡®¿ì¿ï¡¯°ú °ü·ÃµÈ ´ëÈ­ µ¥ÀÌÅ͸¦ ÅäÇÈ ¸ðµ¨¸µ ¹æ¹ý°ú ÅؽºÆ®¸¶ÀÌ´× ±â¹ýÀ¸·Î ºÐ¼®ÇÏ¿© äÆÿ¡¼­ÀÇ ¿ì¿ï °ü·Ã ´ã·ÐÀÇ Æ¯¼ºÀ» ÆľÇÇÏ¿´´Ù. ¶ÇÇÑ, 꺿¿¡¼­ ºó¹øÈ÷ ³ªÅ¸³ª´Â ¡®¿ì¿ï¡¯´ã·ÐÀÇ ¹üÁÖ¿Í Æ®À§ÅÍ ¡®¿ì¿ï¡¯´ã·ÐÀÇ ¹üÁÖÀÇ Â÷ÀÌÁ¡À» ºñ±³ÇÏ¿´´Ù. À̸¦ ÅëÇØ Ãªº¿ µ¥ÀÌÅÍÀÇ ¡®¿ì¿ï¡¯´ëÈ­¸¸ÀÇ Æ¯Â¡À» ÆľÇÇÏ°í, ÀûÀýÇÑ ½É¸®Áö¿ø Á¤º¸¸¦ Á¦°øÇϴ êº¿ ¼­ºñ½º¸¦ À§ÇÑ ½Ã»çÁ¡°ú ÇâÈÄ ¿¬±¸ ¹æÇâ¿¡ ´ëÇØ ³íÀÇÇÑ´Ù.
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(English Abstract)
Influenced by a culture that prefers non-face-to-face activity during the COVID-19 pandemic, chatbot usage is accelerating. Chatbots have been used for various purposes, not only for customer service in businesses and social conversations for fun but also for mental health. Chatbots are a platform where users can easily talk about their depressed moods because anonymity is guaranteed. However, most relevant research has been on social media data, especially Twitter data, and few studies have analyzed the commercially used chatbots data. In this study, we identified the characteristics of depressive discourse in user-chatbot interaction data by analyzing the chats, including the word ¡®depress,¡¯ using the topic modeling algorithm and the text-mining technique. Moreover, we compared its characteristics with those of the depressive moods in the Twitter data. Finally, we draw several design guidelines and suggest avenues for future research based on the study findings.
Å°¿öµå(Keyword) Chatbot   Depressive Discourse   Depressive Moods   Mental Health   꺿   ¿ì¿ï ´ãÈ­   ¿ì¿ï Á¤¼­   Á¤½Å°Ç°­  
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