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    CD40L๋ฅผ ํ‘œ์ ์œผ๋กœ ํ•˜๋Š” ํ‚ค๋ฉ”๋ผํ•ญ์›์ˆ˜์šฉ์ฒด-์œ ๋„ ์กฐ์ ˆ T ์„ธํฌ ๊ฐœ๋ฐœ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜๊ณผํ•™๊ณผ, 2021.8. ์žฅ์ง€์œค.์„œ๋ก : ์กฐ์ ˆ T ์„ธํฌ๋Š” ์ƒ์ฒด ๋‚ด์˜ ๋ฉด์—ญ๋ฐ˜์‘์„ ์กฐ์ ˆํ•˜๊ณ  ์ž์‹ ์˜ ํ•ญ์›์— ๋Œ€ํ•œ ์ž๊ฐ€๋ฉด์—ญ๊ด€์šฉ์„ ์œ ์ง€ํ•˜๋Š” ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์ตœ๊ทผ์—๋Š” ์กฐ์ ˆ T ์„ธํฌ๋ฅผ ์ฃผ์ž…ํ•˜์—ฌ ์ž๊ฐ€๋ฉด์—ญ์งˆํ™˜์„ ์น˜๋ฃŒํ•˜๋Š” ๋™๋ฌผ ๋ชจ๋ธ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ์กฐ์ ˆ T ์„ธํฌ๋Š” ์ƒ์ฒด ๋‚ด์— ๋‚ฎ์€ ๋น„์œจ๋กœ ์กด์žฌํ•˜๋ฏ€๋กœ ์ด๋ฅผ ์‹ค์ œ ์ž„์ƒ์— ์ ์šฉํ•˜๊ธฐ ์œ„ํ•ด ๋ถ„๋ฆฌ ๋ฐ ์ฆ์‹์‹œํ‚ค๋Š” ๊ณผ์ •์— ์–ด๋ ค์›€์ด ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ‚ค๋ฉ”๋ผํ•ญ์›์ˆ˜์šฉ์ฒด(CAR)๋ฅผ ์ด์šฉํ•˜์—ฌ ์ƒ์ฒด ๋‚ด ์กฐ์ ˆ T ์„ธํฌ์˜ ์ˆ˜๋ฅผ ๋Š˜๋ฆฌ๋Š” ๋ฐฉ์•ˆ์„ ๋งˆ๋ จํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. CAR-์œ ๋„ ์กฐ์ ˆ T ์„ธํฌ(iTreg)์€ CD40L์— ํŠน์ด์ ์ธ ๋‹จ์ผ ์‡„ ๊ฐ€๋ณ€ ๋‹จํŽธ(scFv) ๋„๋ฉ”์ธ์„ ๊ฐ€์ง€๊ณ  ์žˆ์–ด, ํ™œ์„ฑํ™”๋œ T์„ธํฌ๊ฐ€ ๋ฐœํ˜„ํ•˜๊ณ  ์žˆ๋Š” CD40L์™€ ๋งŒ๋‚ฌ์„ ๋•Œ, ์‹ ํ˜ธ์ „๋‹ฌ ๋„๋ฉ”์ธ๋“ค์— ์˜ํ•ด์„œ ๋ฏธ๊ฐ์ž‘ T ์„ธํฌ๊ฐ€ ์กฐ์ ˆ T ์„ธํฌ๋กœ ๋ถ„ํ™”ํ•˜๊ฒŒ๋” ๋””์ž์ธ๋˜์—ˆ๋‹ค. ๋ฐฉ๋ฒ•: CAR ๋ฒกํ„ฐ์˜ ๋ฐœํ˜„์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด์„œ ์—ผ๊ธฐ์„œ์—ด๊ฒฐ์ •์„ ์ง„ํ–‰ํ•˜์˜€์œผ๋ฉฐ, HEK293FT ์„ธํฌ์ฃผ์— ํ˜•์งˆ์ „ํ™˜์„ ํ•˜์—ฌ ํ˜•๊ด‘๋ฐœํ˜„์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ฐ”์ด๋Ÿฌ์Šค์˜ ์ž…์ž์˜ ์ˆ˜๋Š” ELISA์™€ Flow cytometry๋กœ ๊ณ„์‚ฐํ•˜์˜€๋‹ค. MACS ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ๋ถ„๋ฆฌํ•œ ๋งˆ์šฐ์Šค ๋ฏธ๊ฐ์ž‘ CD4+ T ์„ธํฌ์— ๋ Œํ‹ฐ ๋ฐ”์ด๋Ÿฌ์Šค๋ฅผ ์ „์ด์‹œ์ผฐ๋‹ค. ์ดํ›„ ๋ฐœํ˜„๋œ CAR์˜ ๊ตฌ์กฐ์ , ๊ธฐ๋Šฅ์  ์ธก๋ฉด์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด์„œ ํ•ญ์ฒด ์—ผ์ƒ‰์„ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ํ‘œํ˜„๊ณผ ๊ธฐ๋Šฅ ๋งˆ์ปค์˜ ๊ฒ€์ถœ์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ: CAR์˜ ๋ฐœํ˜„์€ pLVX-IRES-ZsGreen1 ๋ฐฑํ„ฐ์— ์กด์žฌํ•˜๋Š” ZsGreen (GFP) ํ˜•๊ด‘์œผ๋กœ ํ™•์ธํ•˜์˜€๋‹ค. ๋งˆ์šฐ์Šค ๋ฏธ๊ฐ์ž‘ CD4+ T ์„ธํฌ์— CAR๊ฐ€ ์ „์ด๋œ ์ƒํƒœ์˜ ์„ธํฌ ์™ธ ๋„๋ฉ”์ธ์˜ ๋ฐœํ˜„์€ ์ˆ˜์šฉ์„ฑ CD40L ๋‹จ๋ฐฑ์งˆ์ด scFv์— ๊ฒฐํ•ฉํ•˜๋Š” ๊ฒƒ์„ ํ†ตํ•ด ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋งˆ์šฐ์Šค์˜ ํ™œ์„ฑํ™”๋œ CD3+ T ์„ธํฌ์™€ ํ•จ๊ป˜ ๋ฐฐ์–‘ํ•œ ํ›„, FoxP3 ๋“ฑ์„ ๋ฐœํ˜„ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฒฐ๋ก : ๋ณธ ์—ฐ๊ตฌ์—์„œ ๊ณ ์•ˆ๋œ CAR-iTreg์€ ํ™œ์„ฑํ™”๋œ T ์„ธํฌ์— ์žˆ๋Š” CD40L๋ฅผ ํ‘œ์ ํ•˜๋„๋ก ๋””์ž์ธ๋˜์—ˆ๋‹ค. CD40L์™€ ๊ฒฐํ•ฉํ•œ ํ›„, ์ „์ด๋œ ๋ฏธ๊ฐ์ž‘ CD4+ CAR-T ์„ธํฌ๋“ค์ด ์œ ๋„ ์กฐ์ ˆ T ์„ธํฌ์˜ ๋Œ€ํ‘œ์ ์ธ ์ „์‚ฌ์ธ์ž์ธ FoxP3์™€ ํ‘œ๋ฉด ํ‘œ์ง€์ž๋ฅผ ๋ฐœํ˜„ํ•˜์˜€๊ธฐ์—, ์ž๊ฐ€๋ฉด์—ญ์งˆํ™˜์˜ ์น˜๋ฃŒ ๋ฐ ์ด์‹๊ฑฐ๋ถ€๋ฐ˜์‘ ์–ต์ œ์— ์น˜๋ฃŒ์ œ๋กœ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์‹ค๋งˆ๋ฆฌ๋ฅผ ์ œ๊ณตํ•  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค.Introduction: Regulatory T cells (Tregs) play a role in regulating the immune response in vivo and maintaining self-tolerance that does not cause an autoimmune reaction to our antigen. Recently, studies on adoptive cell transfer of Tregs into an animal model of autoimmune disease are in progress. However, since Tregs exist in a small proportion in vivo, it is known that the process of isolation and proliferation is difficult to apply to actual clinical practice. Therefore, in this study, I used the method to increase the number of Tregs in vivo by using chimeric antigen receptor (CAR). CAR-inducible Treg (iTreg) has a CD40L-specific single-chain variable fragment (scFv), thus when encountering CD40L of stimulated T cells, signals are transmitted by the intracellular domain of CAR, inducing naive T cells to differentiate into Tregs. Methods: To confirm the expression of CAR vector, sequencing was carried out and the fluorescence of CAR-transfected in HEK293FT cell line was identified. The number of virus particles was counted by enzyme-linked immunosorbent assay (ELISA) and flow cytometry. Mouse naรฏve CD4+ T cells were isolated using the magnetic-activated cell sorting (MACS) system, and the previously produced lentivirus was transferred to the enriched naรฏve CD4+ T cells. Afterward, structural and functional aspects of the expressed CAR were verified with markers detected by fluorescence antibody staining. Results: The expression of CAR was checked by ZsGreen fluorescence present in pLVX-IRES-ZsGreen1 vector. The extracellular domain in which the CAR was transduced to mouse naรฏve CD4+ T cells was confirmed by the binding of the soluble CD40L protein to the scFv. In addition, after culturing with activated mouse CD3+ T cells, the expression level of FoxP3 and other surface markers were determined. Conclusions: The CAR-iTreg designed in this study is to target CD40L in activated T cells. After binding to CD40L, the transduced naรฏve CD4+ CAR-T cells acquire the lineage determining transcription factor; FoxP3 and surface markers of Treg cells, giving a potential to be used as a treatment for autoimmune disease and prevention of immunological rejection in transplantation.Introduction 1 Material and methods 9 Results 14 Discussion 52 Reference 56 Abstract in Korean 63์„

    The Effects of Technology and Strategy on Innovation in the Content Industry

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ˜‘๋™๊ณผ์ • ๊ธฐ์ˆ ๊ฒฝ์˜ยท๊ฒฝ์ œยท์ •์ฑ…์ „๊ณต, 2016. 2. ํ™ฉ์ค€์„.์ฝ˜ํ…์ธ ์‚ฐ์—…์—์„œ ๊ธฐ๊ธฐ์— ๊ด€๋ จ๋œ ๊ธฐ์ˆ ํ˜์‹ ์ด ์ง€์†์ ์œผ๋กœ ๋ฐœ์ƒํ•˜๊ณ  ์žˆ๋Š”๋ฐ ๋ฐ˜ํ•˜์—ฌ, ํ˜์‹ ์˜ ํ™•์‚ฐ์€ ์ ์  ๋”๋””๊ฒŒ ์ผ์–ด๋‚˜๊ณ  ์žˆ๋Š” ์–‘์ƒ์„ ๋ณด์ด๊ณ  ์žˆ์œผ๋ฉฐ ์ด๋Š” ๊ธฐ๊ธฐ๊ฐ€ ๋‹ด๊ณ  ์žˆ๋Š” ์ฝ˜ํ…์ธ  ์ž์ฒด์— ๊ด€๋ จํ•œ ํ˜์‹ ์ด ๊ธฐ๊ธฐ์˜ ํ˜์‹ ๊ณผ ๊ท ํ˜•์„ ์ด๋ฃจ๊ณ  ์žˆ์ง€ ๋ชปํ•˜๊ธฐ ๋•Œ๋ฌธ์ด๋ผ๋Š” ํ‰๊ฐ€๊ฐ€ ๊ฑฐ๋ก ๋˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ํ•œ๊ตญ์˜ 2014๋…„ ์ „์ฒด ์ฝ˜ํ…์ธ ์‚ฐ์—… ๋งค์ถœ์•ก์€ 2013๋…„ ๋Œ€๋น„ 3.4% ์ฆ๊ฐ€ํ•œ 94์กฐ 3,000์–ต์›์„ ๊ธฐ๋Œ€ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ 2010๋…„๋ถ€ํ„ฐ ์ง€๊ธˆ๊นŒ์ง€ ์ง€์†์ ์ธ ๋งค์ถœ๊ทœ๋ชจ ์ƒ์Šน์„ธ๋ฅผ ๋ณด์ธ ๋งŒํผ ๊ทธ ์ค‘์š”์„ฑ์ด ์ปค์ง€๊ณ  ์žˆ๋Š” ์‚ฐ์—…์ด๊ธฐ์— ์ฝ˜ํ…์ธ ์‚ฐ์—…์˜ ํ˜์‹  ์—ฐ๊ตฌ๋Š” ๊ตญ๊ฐ€ ์ „์ฒด ๋ฐ ์‚ฐ์—…์ž์ฒด์˜ ์ง€์†์ ์ธ ์„ฑ์žฅ์„ ์œ„ํ•œ ์ดˆ์„์œผ๋กœ์จ ์˜๋ฏธ๊ฐ€ ์žˆ๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ๋Š” ์ฝ˜ํ…์ธ ์‚ฐ์—… ๋‚ด์˜ ๋น„์ฆˆ๋‹ˆ์Šค๋ชจ๋ธ์ด ์ฑ„ํƒํ•œ ๊ธฐ์ˆ ํ˜์‹ ๊ณผ ๋น„๊ธฐ์ˆ ์  ์ „๋žต์ด ์œ ๋„ํ•˜๋Š” ์ฝ˜ํ…์ธ  ํ˜์‹  ๋ฐ ๋‹ค์–‘์„ฑ์„ ๊ด€์ฐฐํ•˜์—ฌ ์ฝ˜ํ…์ธ  ์‚ฐ์—… ๋‚ด์˜ ๋น„์ฆˆ๋‹ˆ์Šค๋ชจ๋ธ๊ณผ ์ •์ฑ…๊ฒฐ์ •์ž๋“ค์—๊ฒŒ ๋„์›€์ด ๋˜๋Š” ํ•จ์˜๋ฅผ ์ด๋Œ๊ณ ์ž ํ•œ๋‹ค. ์ฝ˜ํ…์ธ  ์‚ฐ์—… ๋‚ด์˜ ํ˜์‹ ์€ ๊ธฐ์กด์— ์„œ๋น„์Šค์—…์—์„œ ๋‹ค๋ฃจ์–ด์กŒ๋˜ ํ˜์‹ ๊ณผ ๋”๋ถˆ์–ด ํ†ต์ผ๋œ ๊ฐœ๋…์„ ์ •๋ฆฝํ•˜๊ณ  ํ˜์‹ ์„ฑ๊ณผ๋ฅผ ํ‰๊ฐ€ํ•˜๊ธฐ๊ฐ€ ์–ด๋ ค์›Œ ๊ธฐ์กด์˜ ์—ฐ๊ตฌ์—์„œ๋Š” ๋งŽ์ด ๋‹ค๋ค„์ง€์ง€ ์•Š์€ ์ฃผ์ œ์ด๋‹ค. ํ•˜์ง€๋งŒ ๋ฐฉ์†กํ†ต์‹ ์‚ฐ์—…๊ณผ ๊ฒŒ์ž„์‚ฐ์—… ๋“ฑ์˜ ์ฝ˜ํ…์ธ ์‚ฐ์—…์—์„œ ํ˜์‹ ์€ ๊ธฐ์ˆ ์ ์ธ ์š”์ธ๊ณผ ๋น„๊ธฐ์ˆ ์ ์ธ ์š”์ธ์˜ ํ˜ผํ•ฉ์—์„œ ์ด๋ฃจ์–ด ์ง„๋‹ค๋Š” ์„ ํ–‰์—ฐ๊ตฌ์™€, ๋น„๊ธฐ์ˆ ์  ์š”์ธ์—์„œ๋„ ์œ ํ†ต, ๋ฏธ๋””์–ด ํ˜•ํƒœ, ์ฝ˜์…‰, ์‚ฌ์šฉ์ž ์ธํ„ฐํŽ˜์ด์Šค ๋“ฑ์˜ ์ „๋žต์ด ํฐ ์ถ•์œผ๋กœ ์กด์žฌํ•œ๋‹ค๋Š” ๊ฒƒ์— ์ดˆ์ ์„ ๋งž์ถ”์–ด ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ๋Š” ์ฝ˜ํ…์ธ ์‚ฐ์—… ๋‚ด์˜ ๋น„์ฆˆ๋‹ˆ์Šค๋ชจ๋ธ์„ ๊ธฐ์ˆ ํ˜์‹ , ๋น„๊ธฐ์ˆ ์  ์ „๋žต์˜ ์ฑ„ํƒ ์œ ๋ฌด์— ๋”ฐ๋ผ ๋„ค ๊ฐ€์ง€๋กœ ๋ถ„๋ฅ˜ํ•˜๊ณ , ์œ ์ „์•Œ๊ณ ๋ฆฌ์ฆ˜(Genetic Algorithm)์„ ํ™œ์šฉํ•˜์—ฌ ๊ฐ ๋ชจ๋ธ์ด ์‹œ๊ฐ„์ด ์ง€๋‚จ์— ๋”ฐ๋ผ ์–ด๋– ํ•œ ํ˜์‹  ์„ฑ๊ณผ์™€ ์ฝ˜ํ…์ธ  ๋‹ค์–‘์„ฑ์„ ๋ณด์ด๋Š”์ง€ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ๊ธฐ์ˆ ํ˜์‹ ๊ณผ ๋น„๊ธฐ์ˆ ์  ์ „๋žต ๋ชจ๋‘ ์ฑ„ํƒํ•œ ๋น„์ฆˆ๋‹ˆ์Šค๋ชจ๋ธ์˜ ํ˜์‹ ์„ฑ๊ณผ๊ฐ€ ์žฅ๊ธฐ์ ์œผ๋กœ ์„ฑ์žฅํ•˜๋Š” ํ˜•ํƒœ๋ฅผ ๋ ๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, ๋น„๊ธฐ์ˆ ์  ์ „๋žต๋งŒ ์ฑ„ํƒํ•˜๊ฑฐ๋‚˜ ์•„๋ฌด๊ฒƒ๋„ ์ฑ„ํƒํ•˜์ง€ ์•Š์€ ๋น„์ฆˆ๋‹ˆ์Šค๋ชจ๋ธ์€ ์žฅ๊ธฐ์ ์œผ๋กœ ์„ฑ์žฅํ•˜์ง€ ์•Š๋Š” ํ˜์‹ ์„ฑ๊ณผ๋ฅผ ๋ณด์ž„์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋น„๊ธฐ์ˆ ์ ์ธ ์ „๋žต์€ ๊ทธ ๋‹จ๋…์œผ๋กœ ์‚ฌ์šฉ๋˜์—ˆ์„ ๋•Œ์— ์žฅ๊ธฐ์ ์œผ๋กœ ์•„๋ฌด๊ฒƒ๋„ ๋„์ž…๋˜์ง€ ์•Š๋Š” ๋น„์ฆˆ๋‹ˆ์Šค๋ชจ๋ธ๋ณด๋‹ค ๋‚ฎ์€ ํ˜์‹ ์„ฑ๊ณผ ์ฆ๊ฐ€์œจ์„ ๋ณด์˜€๋‹ค. ์ด๋Š” ๋น„๊ธฐ์ˆ ์ ์ธ ์ „๋žต์€ ๊ธฐ์ˆ ํ˜์‹ ์ด ๊ฐ™์ด ๋„์ž…๋˜์—ˆ์„ ๋•Œ ํ•จ๊ป˜ ์‹œ๋„ˆ์ง€ ํšจ๊ณผ๋ฅผ ๋‚ด์ง€๋งŒ, ๋‹จ๋…์œผ๋กœ ์‚ฌ์šฉ๋˜์—ˆ์„ ๋•Œ์—๋Š” ์˜คํžˆ๋ ค ๋น„ํšจ์œจ์„ ๊ฐ€์ ธ์˜จ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ชจ๋“  ์‹คํ—˜์—์„œ ์ฝ˜ํ…์ธ ์˜ ๋‹ค์–‘์„ฑ์€ ์ฆ๊ฐ€ํ•˜์ง€๋„, ๊ฐ์†Œํ•˜์ง€๋„ ์•Š์•˜์œผ๋ฉฐ ์ด๋Š” ๊ธฐ์ˆ ํ˜์‹ ๊ณผ ๋น„๊ธฐ์ˆ ์  ์ „๋žต์€ ์ฝ˜ํ…์ธ  ์ฐฝ์˜์„ฑ์˜ ํ™•์žฅ์—๋Š” ์˜ํ–ฅ์„ ๋ผ์น˜์ง€ ์•Š์œผ๋ฉฐ ์ด๋ฅผ ์œ„ํ•ด์„œ๋Š” ๋‹ค๋ฅธ ์š”์ธ์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ํ˜์‹ ์„ฑ๊ณผ์— ๊ด€๋ จ๋œ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋Š” ์‹ค์ œ ํ•œ๊ตญ์˜ ๋ฐฉ์†กํ†ต์‹  ์ฝ˜ํ…์ธ ์‚ฐ์—…์—์„œ ์‹œ์ฒญ๋ฅ  ๋ณ€ํ™”์™€ ๋น„์Šทํ•œ ์ถ”์ด๋ฅผ ๋ณด์˜€์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์ฝ˜ํ…์ธ ์‚ฐ์—…์—์„œ์˜ ํ˜์‹ ์„ฑ์€ ์ˆ˜์šฉ์ž์˜ ๋‹ˆ์ฆˆ๋ฅผ ์–ผ๋งˆ๋‚˜ ์ž˜ ๋ฐ˜์˜ํ•˜๋Š”์ง€์˜ ๊ด€์ ์„ ์˜๋ฏธํ•œ๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๊ฒ ๋‹ค. ๋ณธ์—ฐ๊ตฌ๋Š” ์ด์™€ ๊ฐ™์€ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์ฝ˜ํ…์ธ ์‚ฐ์—… ๋‚ด์˜ ๋น„์ฆˆ๋‹ˆ์Šค๋ชจ๋ธ์˜ ๊ฒฝ์˜์ „๋žต ๋ฐ ์ •์ฑ…๊ฒฐ์ •์ž์—๊ฒŒ ์ฝ˜ํ…์ธ ์‚ฐ์—… ๋‚ด ํ˜์‹ ์˜ ๋ฐฉํ–ฅ์„ฑ์„ ์ œ์‹œํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.1. ์„œ๋ก  1 2. ์ด๋ก ์  ๋ฐฐ๊ฒฝ 7 2.1 ์ง„ํ™”๋ก ์  ๊ด€์ ์—์„œ์˜ ํ˜์‹  7 2.2 ์ฝ˜ํ…์ธ  ์‚ฐ์—… ๋‚ด์˜ ํ˜์‹  10 2.3 ์ฝ˜ํ…์ธ  ์‚ฐ์—… ํ‰๊ฐ€ ์š”์†Œ 13 3. ์—ฐ๊ตฌ ์„ค๊ณ„ 15 3.1 ์—ฐ๊ตฌ ๊ฐœ์š” 15 3.2 ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•๋ก  16 3.2.1 ์œ ์ „์•Œ๊ณ ๋ฆฌ์ฆ˜(Genetic Algorithm, GA) 16 3.2.2 ์œ ์ „์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์—ฐ์‚ฐ 17 3.3 ์—ฐ๊ตฌ ๋ชจ๋ธ 20 3.3.1 ๋ณ€์ˆ˜ 22 3.3.2 ์‹คํ—˜์˜ ๊ฐ€์ • 24 4. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ 29 4.1 ์ฝ˜ํ…์ธ  ํผํฌ๋จผ์Šค ๋ถ„์„ 29 4.1.1 ์‹คํ—˜1: ๊ธฐ์ˆ ํ˜์‹ ๊ณผ ๋น„๊ธฐ์ˆ ์  ์ „๋žต์„ ์ทจํ•˜์ง€ ์•Š์„ ๋•Œ 29 4.1.2 ์‹คํ—˜2: ๊ธฐ์ˆ ํ˜์‹ ์„ ์ทจํ•  ๋•Œ 30 4.1.3 ์‹คํ—˜3: ๋น„๊ธฐ์ˆ ์  ์ „๋žต์„ ์ทจํ•  ๋•Œ 31 4.1.4 ์‹คํ—˜4: ๊ธฐ์ˆ ํ˜์‹ ๊ณผ ๋น„๊ธฐ์ˆ ์  ์ „๋žต์„ ๋ชจ๋‘ ์ทจํ•  ๋•Œ 32 4.2 ์ฝ˜ํ…์ธ  ๋‹ค์–‘์„ฑ ๋ฐ ๋ถ„ํฌ ๋ถ„์„ 34 5. ๊ฒฐ๋ก  ๋ฐ ์‹œ์‚ฌ์  37 6. ํ•œ๊ณ„์  45 ์ฐธ๊ณ ๋ฌธํ—Œ 47 ๋ถ€๋ก 53 ๋ถ€๋ก 1 : (์ฝ˜ํ…์ธ  ํ˜์‹ ์„ฑ ์‹คํ—˜ 1 ๊ฒฐ๊ณผ๊ฐ’) 53 ๋ถ€๋ก 2 : (์ฝ˜ํ…์ธ  ํ˜์‹ ์„ฑ ์‹คํ—˜ 2 ๊ฒฐ๊ณผ๊ฐ’) 54 ๋ถ€๋ก 3 : (์ฝ˜ํ…์ธ  ํ˜์‹ ์„ฑ ์‹คํ—˜ 3 ๊ฒฐ๊ณผ๊ฐ’) 55 ๋ถ€๋ก 4 : (์ฝ˜ํ…์ธ  ํ˜์‹ ์„ฑ ์‹คํ—˜ 4 ๊ฒฐ๊ณผ๊ฐ’) 56 ๋ถ€๋ก 5 : (์ฝ˜ํ…์ธ  ๋‹ค์–‘์„ฑ ์‹คํ—˜ ๊ฒฐ๊ณผ๊ฐ’) 57 ๋ถ€๋ก 6 : (์ฝ˜ํ…์ธ  ํ˜์‹ ์„ฑ๊ณผ ๋ถ„ํฌ ์‹คํ—˜ 1 ๊ฒฐ๊ณผ๊ฐ’) 58 ๋ถ€๋ก 7 : (์ฝ˜ํ…์ธ  ํ˜์‹ ์„ฑ๊ณผ ๋ถ„ํฌ ์‹คํ—˜ 4 ๊ฒฐ๊ณผ๊ฐ’) 59 Abstract 60Maste

    Focusing on the Korean Media Market

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๊ธฐ์ˆ ๊ฒฝ์˜ยท๊ฒฝ์ œยท์ •์ฑ…์ „๊ณต,2020. 2. ํ™ฉ์ค€์„.๋ฏธ๋””์–ด ์‹œ์žฅ ๋‚ด์˜ ๊ธฐ์ˆ  ๋ฐœ์ „์€ ์ด์šฉ์ž์˜ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ์„ ๋‹ค์–‘ํ•œ ์ฐจ์›์—์„œ ๋ณ€ํ™”์‹œ์ผœ ๋†“์•˜๋‹ค. ํŠนํžˆ ์ธํ„ฐ๋„ท, ์ง„๋ณด๋œ ๋„คํŠธ์›Œํ‚น ๊ธฐ์ˆ , ์Šค๋งˆํŠธ ๋””๋ฐ”์ด์Šค์˜ ๋“ฑ์žฅ์€ ์ด์šฉ์ž๋“ค์ด ๋‹ค์–‘ํ•œ ๋ฏธ๋””์–ด ์ฝ˜ํ…์ธ ๋ฅผ ์‹œ๊ฐ„์ , ๊ณต๊ฐ„์  ์ œ์•ฝ ์—†์ด ์ฆ๊ธธ ์ˆ˜ ์žˆ๋Š” ๋ฏธ๋””์–ด ํ™˜๊ฒฝ์„ ์ œ๊ณตํ•˜์˜€๋‹ค. ๊ณผ๊ฑฐ ๋ฏธ๋””์–ด ์—ฐ๊ตฌ๋“ค์€ ์ด๋Ÿฌํ•œ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ์„ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ฏธ๋””์–ด ์ƒํƒœ๊ณ„๋ผ๋Š” ๊ฐœ๋…์œผ๋กœ ์„ค๋ช…ํ–ˆ๋‹ค. ์ด๋Š” ๋ฏธ๋””์–ด ํ™˜๊ฒฝ ๋‚ด์˜ ์š”์ธ๋“ค, ์ฆ‰, ๋ฏธ๋””์–ด, ๊ธฐ์ˆ , ์ด์šฉ์ž, ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜์„ ๊ตฌ๋ถ„ ์ง“๋Š” ๊ฒƒ์ด ๋ฌด์˜๋ฏธํ•ด์ง€๊ณ  ๋””์ง€ํ„ธ-์•„๋‚ ๋กœ๊ทธ, ์ฃผ๋ฅ˜-๋น„์ฃผ๋ฅ˜, ์ „ํ†ต-๋‰ด๋ฏธ๋””์–ด์˜ ๊ฒฝ๊ณ„๊ฐ€ ๋ชจํ˜ธํ•ด์ง€๋Š” ํ˜„์ƒ์„ ๋ฌ˜์‚ฌํ•˜๋Š” ๊ฐœ๋…์ด๋‹ค. ์ด๋Ÿฌํ•œ ํ˜„๋Œ€ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ ํ•˜์—์„œ ๋ฏธ๋””์–ด ์—ฐ๊ตฌ๋“ค์€ ์ ์  ๋ฏธ๋””์–ด, ๊ธฐ์ˆ , ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜๊ณผ ๊ฐ™์€ ์š”์ธ๋ณด๋‹ค ์ด์šฉ์ž์˜ ์—ญํ•  ๋น„์ค‘์ด ๋†’์•„์ง€๋Š” ๊ฒƒ์— ๋Œ€ํ•ด ์ดˆ์ ์„ ๋งž์ถฐ์™”๋‹ค. ํŠนํžˆ Web 2.0์ด ์ ์šฉ๋œ ๋ฏธ๋””์–ด ์„œ๋น„์Šค๋“ค์˜ ์ง€์†์  ๋“ฑ์žฅ์€ ์ด์šฉ์ž์—๊ฒŒ ์ƒ์‚ฐ์ž์™€ ์†Œ๋น„์ž์˜ ์—ญํ• ์„ ๋ชจ๋‘ ๋ถ€์—ฌํ•˜๋Š” ํ”„๋กœ์Šˆ๋จธ(prosumer) ์˜ ๊ฐœ๋…์„ ์ ์šฉํ•˜๊ฒŒ ํ•˜์˜€๋‹ค. ์ด์šฉ์ž๋“ค์€ ์Šค์Šค๋กœ ์ž์‹ ์ด ์›ํ•˜๋Š” ์ง€์‹๊ณผ ์ •๋ณด๋ฅผ ๋‹ด์€ ์ฝ˜ํ…์ธ ๋ฅผ ์ œ์ž‘ํ•˜๊ณ  ์ด๋ ‡๊ฒŒ ์ œ์ž‘๋œ ์‚ฌ์šฉ์ž ์ œ์ž‘ ์ฝ˜ํ…์ธ  (User-generated Content, UGC)๋“ค์€ ๋‹ค์‹œ ๋‹ค๋ฅธ ์ด์šฉ์ž๋“ค์˜ ํ–‰๋™์— ์˜ํ–ฅ์„ ๋ผ์น˜๊ฑฐ๋‚˜ ๋‹ค๋ฅธ ๋ฏธ๋””์–ด ์ฝ˜ํ…์ธ , ๋” ๋‚˜์•„๊ฐ€ ์ฃผ๋ฅ˜ ๋ฏธ๋””์–ด ์‹œ์žฅ๊นŒ์ง€ ๋ณ€ํ™”์‹œํ‚ค๊ธฐ์— ์ด๋ฅด๋ €๋‹ค. UGC ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ด์šฉ์ž๋“ค์ด ์ƒ์„ฑํ•˜๋Š” ์†Œ์…œ ๋„คํŠธ์›Œํฌ ํ˜น์€ ์ง‘๋‹จ์ง€์„ฑ์€ ๊ธฐ์—…์˜ ์ž์‚ฐ์œผ๋กœ์จ ํ™œ์šฉ๋˜๊ธฐ๋„ ํ•˜๋Š” ๋“ฑ ์ด์šฉ์ž์˜ ์ฐธ์—ฌ๋Š” ํ˜„๋Œ€ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ ๋‚ด์˜ ์ง€์†์  ๊ฐ€์น˜ ์ฐฝ์ถœ์„ ๋‹ด๋‹นํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ˜„๋Œ€ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ์˜ ๊ด€์ ์—์„œ ์ •๋ณด ๋ฐ ์ง€์‹ ์ฝ˜ํ…์ธ ๋ฅผ ์ƒ์„ฑ, ๊ณต์œ , ์ˆ˜์ •, ์ด์šฉํ•˜๋Š” ์ง€์‹ ํ™œ๋™์— ๋Œ€ํ•œ ์ด์šฉ์ž์˜ ์ฐธ์—ฌ๋ฅผ ์ดํ•ดํ•˜๋Š” ๋ฐ์— ๋ชฉ์ ์ด ์žˆ๋‹ค. ์ด์šฉ์ž, ๋ฏธ๋””์–ด, ์ฝ˜ํ…์ธ ์˜ ๊ด€๊ณ„๋ฅผ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ์˜ ๊ด€์ ์—์„œ ์ดํ•ดํ•˜๊ณ , ์—ฐ๊ตฌ์˜ ๊ฒฐ๋ก ์—์„œ ์ง€์† ๊ฐ€๋Šฅํ•œ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ์„ ํ˜•์„ฑํ•˜๋Š” ์ด๋“ค์˜ ๊ด€๊ณ„์™€ ์—ญํ• , ์ด๋ฅผ ํ™œ์šฉํ•˜๋Š” ๋ฐฉ์•ˆ์„ ์ œ์•ˆํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ•œ๊ตญ์ •๋ณดํ†ต์‹ ์ •์ฑ…์—ฐ๊ตฌ์›์—์„œ ๋งค๋…„ ์กฐ์‚ฌํ•˜๋Š” ๋ฏธ๋””์–ด ํŒจ๋„ ๋ฐ์ดํ„ฐ์˜ 2018๋…„๋„ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ํ•œ๊ตญ ์ธ๊ตฌ ์•ฝ ๋งŒ ๋ช…์„ ์˜จ๋ผ์ธ ์ง€์‹ ํ™œ๋™ ์ฐธ์—ฌ ์ •๋„์— ๋”ฐ๋ผ ์ ๊ทน์  ์ฐธ์—ฌ์ž, ์†Œ๊ทน์  ์ฐธ์—ฌ์ž, ๋ฐฉ๊ด€์ž๋กœ ๋ถ„๋ฅ˜ํ•ด ๋ณธ๋‹ค. ๋ถ„๋ฅ˜์—๋Š” K-means ํด๋Ÿฌ์Šคํ„ฐ๋ง ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ˆœ์œ„ ํ”„๋กœ๋น— (Ordered Probit) ๋ชจํ˜•๊ณผ ์ตœ์†Œ ์ œ๊ณฑ ํšŒ๊ท€ ๋ชจํ˜• (Ordinary Least Squares regression)์„ ํ™œ์šฉํ•˜์—ฌ ๊ฐ ๋ชจํ˜•์—์„œ ์–ด๋– ํ•œ ๋ฏธ๋””์–ด ์ด์šฉ์ด ์ด์šฉ์ž๋“ค์„ ์ ๊ทน์  ์ฐธ์—ฌ์ž๋กœ ์œ ์ธํ•˜๋Š”์ง€, ์ด์šฉ์ž ์ฐธ์—ฌ ๊ทธ๋ฃน์— ๋”ฐ๋ฅธ ๋ฏธ๋””์–ด ์ด์šฉ ํŒจํ„ด์ด ์–ด๋–ป๊ฒŒ ๋‹ค๋ฅธ์ง€ ํ™•์ธํ•œ๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ์ง€์‹ ์œ ์ž…๊ณผ ์ ‘๊ทผ์„ฑ์˜ ์ธก๋ฉด์—์„œ ๋‰ด๋ฏธ๋””์–ด์™€ ์ „ํ†ต๋ฏธ๋””์–ด๊ฐ€ ๋‹ด๋‹นํ•˜๋Š” ์—ญํ• ์ด ๋‚˜๋‰˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ํŠนํžˆ ์ ๊ทน์  ์ฐธ์—ฌ์ž์˜ ์ฐธ์—ฌ๋ฅผ ๋Š˜์ด๋Š” ๋ฐ์—๋Š” ์Šค๋งˆํŠธ ๋””๋ฐ”์ด์Šค๋งŒ์ด ์œ ์˜ํ•œ ์˜ํ–ฅ์„ ๋ผ์น˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์ด์šฉ์ž๋“ค์˜ ์ฐธ์—ฌ๋กœ ์ƒ์‚ฐ๋œ ์ง€์‹ ์ฝ˜ํ…์ธ ๊ฐ€ ๋‹ค์‹œ ์ด์šฉ์ž๋“ค์˜ ํ–‰๋™๋ณ€ํ™”๋ฅผ ์•ผ๊ธฐํ•˜๋Š”์ง€ ํ™•์ธํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ฒŒ์ž„ ์‚ฐ์—…์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ๊ฒŒ์ž„ ์‚ฐ์—…์€ ๋‚ด์—์„œ๋Š” ๊ฒŒ์ž„ ๊ด€๋ จ ์ •๋ณด ์ฝ˜ํ…์ธ ๊ฐ€ ๋‹ค์–‘ํ•œ ๋ฏธ๋””์–ด์—์„œ ๊ณต์œ  ๋ฐ ์ƒ์‚ฐ๋˜๋Š”๋ฐ, ์ด๋“ค ๋ฏธ๋””์–ด๋Š” ๊ฐ๊ธฐ ๋‹ค๋ฅธ ์ •๋„์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ์ œ๊ณตํ•œ๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ์˜จ๋ผ์ธ ์ปค๋ฎค๋‹ˆํ‹ฐ์—์„œ ์ด์šฉ์ž๋“ค์ด ์ƒ์‚ฐํ•ด๋‚ด๋Š” ๊ฒŒ์ž„ ๊ด€๋ จ ์ •๋ณด ์ฝ˜ํ…์ธ ๊ฐ€ ์ด์šฉ์ž๋“ค์ด ๊ด€๋ จ ๊ฒŒ์ž„์— ๋Œ€ํ•ด ๊ธ์ •์ ์ธ ํƒœ๋„๋ฅผ ๊ฐ€์ง€๊ณ , ๋†’์€ ์ด์šฉ ์˜๋„๋ฅผ ๊ฐ€์ง€๊ฒŒ ํ•˜๋Š” ๋ฐ์— ๊ฐ€์žฅ ํฐ ์˜ํ–ฅ์„ ๋ผ์น˜๊ฒŒ ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋Š” ์ด์šฉ์ž๋“ค์ด ํ–‰๋™ ๋ณ€ํ™”๊ฐ€ ์ด์šฉ์ž๋“ค์ด ์ƒ์‚ฐํ•ด๋‚ธ ์ง€์‹ ์ฝ˜ํ…์ธ ์— ์˜ํ•ด ์˜ํ–ฅ์„ ๋ผ์น˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•œ ์—ฐ๊ตฌ์ด๊ธฐ๋„ ํ•˜์ง€๋งŒ, ๊ฒŒ์ž„ ๊ด€๋ จ ๋ฏธ๋””์–ด(์˜จ๋ผ์ธ ์ปค๋ฎค๋‹ˆํ‹ฐ)์™€ ๊ฒŒ์ž„์ด๋ผ๋Š” ๋ฏธ๋””์–ด๊ฐ€ ์–ด๋–ป๊ฒŒ ์ด์šฉ์ž๋“ค์— ์˜ํ•ด ์ƒํ˜ธ์ž‘์šฉํ•˜๊ณ  ์ง€์† ๊ฐ€๋Šฅํ•œ ์ƒํƒœ๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š”์ง€ ํ™•์ธํ•œ ์—ฐ๊ตฌ์ด๊ธฐ๋„ ํ•˜๋‹ค. ์„ธ ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ๋ฏธ๋””์–ด ์‚ฐ์—…์—์„œ ์ด์šฉ์ž๋“ค์˜ ๊ณผ๋„ํ•œ ์ฐธ์—ฌ์™€ ์ƒํ˜ธ์ž‘์šฉ์œผ๋กœ ์ธํ•ด ์ƒ๊ธฐ๋Š” ์‹ฌ๋ฆฌ์  ์ŠคํŠธ๋ ˆ์Šค์™€ ํ”ผ๋กœ๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ๋ฏธ๋””์–ด ์‚ฌ์šฉ์ด ์ด์šฉ์ž๋“ค์˜ ์‹ฌ๋ฆฌ์  ๊ฑด๊ฐ•์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ผ์น˜๋Š”์ง€ ์ง์ ‘์ , ๊ฐ„์ ‘์  ์—ญํ• ์„ ์‚ดํŽด๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ๋ฏธ๋””์–ด ์ด์šฉ์ด ์ง€์‹ ์ฐธ์—ฌ๋ฅผ ์ด‰์ง„ํ•˜์—ฌ ์ƒ๊ธฐ๋Š” ๊ฐ„์ ‘์  ์˜ํ–ฅ์œผ๋กœ ์‹ฌ๋ฆฌ์  ๊ฑด๊ฐ•์— ์–‘์˜ ์˜ํ–ฅ์„ ๋ผ์น˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ˜„๋Œ€ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ์˜ ์ง€์† ๊ฐ€๋Šฅ์„ฑ์„ ์œ„ํ•œ ๋ฏธ๋””์–ด์™€ ์ด์šฉ์ž์˜ ๋ฐ”๋žŒ์งํ•œ ๊ด€๊ณ„, ์ด์šฉ์ž ์ฐธ์—ฌ์˜ ์—ญํ• ์„ ์ œ์‹œํ•˜๊ธฐ ์œ„ํ•ด ๋ฏธ๋””์–ด ํ™˜๊ฒฝ ๋‚ด์˜ ์‚ฌ์šฉ์ž์™€ ๋ฏธ๋””์–ด์˜ ๊ด€๊ณ„๋ฅผ ์‚ดํŽด๋ณด์•˜๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์ด์šฉ์ž๋“ค์˜ ์ง€์‹ ์ƒ์‚ฐ ํ™œ๋™๊ณผ ์ฐธ์—ฌ์— ๋ฏธ๋””์–ด๊ฐ€ ์–ด๋– ํ•œ ์—ญํ• ์„ ๋ฏธ์น˜๋Š”์ง€, ์ด๋ฅผ ๋„˜์–ด ๋ฏธ๋””์–ด์˜ ๊ฑด๊ฐ•ํ•œ ์ฐธ์—ฌ ์ด‰์ง„ ์—ญํ• ์ด ์–ด๋– ํ•œ์ง€๋ฅผ ์‚ดํŽด๋ณด์•˜๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์ „ํ†ต์  ๋ฏธ๋””์–ด์™€ ๋‰ด๋ฏธ๋””์–ด๊ฐ€ ๊ฐ๊ธฐ ๋‹ค๋ฅธ ์ƒํ˜ธ์ž‘์šฉ์˜ ๋ ˆ๋ฒจ์„ ํ†ตํ•ด ์ด์šฉ์ž๋“ค์—๊ฒŒ ๋‹ค๋ฅธ ์˜ํ–ฅ์„ ๋ผ์น˜๊ณ  ์žˆ๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ด์šฉ์ž๋“ค์ด ์ƒ์„ฑํ•ด๋‚ด๋Š” ์ง€์‹ ์ฝ˜ํ…์ธ ๋Š” ๋‹ค์–‘ํ•œ ๋ฏธ๋””์–ด๋ฅผ ์„œ๋กœ ์—ฐ๊ฒฐ์ง€์Œ์œผ๋กœ์จ ์ด์šฉ์ž ์ฐธ์—ฌ๊ฐ€ ๋†’์„์ˆ˜๋ก ๋ฏธ๋””์–ด ์ƒํƒœ๊ณ„๋ฅผ ํ™•์žฅํ•˜๊ณ , ์ง€์† ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๋‰ด ๋ฏธ๋””์–ด๊ฐ€ ์ˆ˜ํ–‰ํ•˜๋Š” ์—ญํ• , ๋ฏธ๋ž˜์— ๋ฐœ์ „ํ•ด ๋‚˜๊ฐ€์•ผ ํ•  ๋ฐฉํ–ฅ์„ ์ด์šฉ์ž๋“ค์˜ ์ฐธ์—ฌ ์ด‰์ง„์„ ํ†ตํ•œ ์ง€์† ๊ฐ€๋Šฅํ•œ ๋ฏธ๋””์–ด ์ƒํƒœ๊ณ„ ๊ตฌ์„ฑ์œผ๋กœ ์ œ์•ˆํ•˜๋Š” ๋ฐ”์ด๋‹ค. ๋˜ํ•œ, ์ง€์† ๊ฐ€๋Šฅํ•œ ๋ฏธ๋””์–ด ํ™˜๊ฒฝ ์œ ์ง€๋ฅผ ์œ„ํ•ด ๋‹ค์Œ์˜ ๋‘ ๊ฐ€์ง€ ์ „๋žต์„ ์ œ์•ˆํ•œ๋‹ค. ์ฒซ์งธ, ๋ฏธ๋””์–ด ํ™˜๊ฒฝ์—์„œ ์ค‘์š”ํ•œ ๊ฐ€์น˜์ธ ์ด์šฉ์ž ์ƒ์„ฑ ์ง€์‹์˜ ์ง€์†์  ์ƒ์‚ฐ์„ ์œ„ํ•ด ์ „ํ†ต ๋ฏธ๋””์–ด์™€ ๋‰ด๋ฏธ๋””์–ด๊ฐ€ ์„œ๋กœ์˜ ์—ญํ• ์„ ๋ณด์™„ํ•˜๊ณ  ์ ์ ˆํžˆ ์ž˜ ์ด์šฉ๋˜์–ด์•ผ ํ•œ๋‹ค. ๋‘˜์งธ, ๋ฏธ๋””์–ด ์ „๋ฌธ๊ฐ€๋“ค์€ ์ด์šฉ์ž ์ฐธ์—ฌ๊ฐ€ ๋งค๊ฐœํ•˜๋Š” ๋ฏธ๋””์–ด ๊ฐ„ ์ƒํ˜ธ์ž‘์šฉ์˜ ๋งค์ปค๋‹ˆ์ฆ˜์„ ์ดํ•ดํ•˜๊ณ  ์ด๋ฅผ ๋ฏธ๋””์–ด ์„œ๋น„์Šค ๊ฐœ๋ฐœ ๋ฐ ์œ ์ง€์— ํ™œ์šฉํ•ด์•ผ ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ๋ฏธ๋””์–ด๋ฅผ ํ™œ์šฉํ•˜๋Š” ์‚ฐ์—…์—์„œ ์ด์šฉ์ž๋“ค์„ ์œ„ํ•œ ๋งˆ์ผ€ํŒ…์„ ์ˆ˜๋ฆฝํ•˜๊ณ , ์ด์šฉ์ž๋“ค์˜ ์ฐธ์—ฌ๋ฅผ ํ†ตํ•ด ๋‹ฌ์„ฑํ•ด์•ผ ํ•˜๋Š” ์ •์ฑ…์  ๋ชฉํ‘œ์™€ ์†Œ์…œ ์ด๋…ธ๋ฒ ์ด์…˜์„ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ์•ˆ ์ˆ˜๋ฆฝ์„ ์œ„ํ•ด ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.Technological advances in the media market have changed the media environment for users in all aspects. In particular, the advent of the Internet, smart devices, and advanced networking technologies provide an environment in which users enjoy diverse media content without limitation of space and time. Past studies explained these changes in the media environment with the concept of hybrid media ecology, which elucidates the phenomenon that blurs the boundaries between the factors existing in the media environment, thereby making it difficult to distinguish them. In light of these changes, media studies have focused on the increasing role of users rather than other players in the media environment such as media, technology, and communication. Especially, with the advent of Web 2.0, users role as a prosumer, a combination of producer and consumer, assumes significance. Users themselves prepare their knowledge content, and this user-generated content has influenced the behavior of other users, the media content market, and the mainstream media. In addition, social networks and collaborative intelligence generated by users have been utilized as the firms assets. This study aims to understand users participation in knowledge activities such as creating, sharing, modifying, using information, and knowledge content, from the perspective of the media environment. By examining the association between the user, media, and knowledge content, intermedia relationship with users participation, and media-user interactions which create a sustainable media environment are recommended. Three studies are used to verify the hypothesis using empirical analyses. Chapter 3 examines how different types of media influence users participation in the online community as a knowledge producer. First, the K-means clustering algorithm is used for segregating users into three groups based on their level of participation in online knowledge production, and I named the groups active participants, passive participants, and bystanders. The Ordered Probit regression is applied to identify factors for making users active participants. Lastly, Ordinary Least Squares regression is used to confirm media usage pattern differences between these user groups. The analyses involved 9,426 individuals from the Korea Media Panel (KMP) data, provided by the Korea Information Society Development Institute (KISDI). The results indicate that, in terms of knowledge acquisition and accessibility, new media and traditional media play different roles. In particular, only smart devices have a significant impact on increasing active participants' participation. Chapter 4 confirms the hypothesis that knowledge content produced by user participation motivates users to change their behavior again. In the gaming industry, people share and produce game-related information on a variety of media platforms, and these outlets have various modes of communication between the information senders and the receivers. Structural Equation Modelling (SEM) is used to build the research framework to recognize the intermedia relationship between the game and game-related media. The results indicate that the online community having game-related information produced by users has the greatest influence on users attitude on the game and users intention to play it. This chapter also identifies the intermedia relationship between the game and game-related media (online communities and live streaming services) and how they interact with each other. Users experience from game playing generates users attitude towards the game, and this attitude influences users intention to utilize game-related media. Conversely, users attitude towards game-related media affects users intention to play the game. In other words, the game generates user-generated content comprising game information, and user-generated game content prompts other users to actually play the game. Chapter 5 focuses on the moderating effect of user participation towards the impact of media usage on users psychological well-being. Users psychological well-being is an important factor in the media environment. Not only does it lead to users continuous use of media, but importantly, it is also considered as a criterion by media policymakers to implement regulation or deregulation of the media services. The direct and indirect effects of media usage on users psychological well-being were investigated. The results indicate that media usage has a negative or an insignificant effect on users' psychological health directly, but there could be indirect positive effects of media usage, which promote users' knowledge participation and has a positive effect on psychological health. In order to recommend factors for the sustainability of a contemporary media environment, this study looked at the role of media in users knowledge production activities and participation, as well as the function of media in healthy participation and intermedia relationships. The results showed that traditional and new media have different influences on users through different levels of interaction. In addition, the knowledge content generated by users connect various media with each other, allowing the media ecosystem to expand and make it sustainable. Therefore, this study proposed the role played by new media and the direction towards which it should develop in the future as constructing a sustainable media ecosystem through the promotion of user participation. In addition, two strategies are proposed to maintain a sustainable media environment: First, traditional and new media should complement each other's roles and be properly used for the continuous production of user-generated knowledge, which holds an important value in the media environment. Second, media professionals should understand the mechanism of intermedia interaction mediated by users participation and utilize it to develop and maintain media services. The results of this study could be used to establish marketing strategies in industries that utilize the media to establish policy goals and achieve social innovation that should be accomplished through user participation.Chapter 1. Introduction 1 1.1 Research Background 1 1.2 Problem Statement 4 1.3 Research Objectives 7 1.4 Research Question 9 1.5 Thesis Outline 11 Chapter 2. Literature Review 14 2.1 Media Environment 14 2.2 Media Research Evolution 17 2.3 User participation and knowledge production 21 2.4 User communication in media environment 31 2.5 Sustainability of Media Environment 34 2.6 Media landscape in South Korea 36 Chapter 3. The Role of Media in User Participation in Knowledge Process: Focusing on the Online Space 39 3.1 Introduction 39 3.2 Literature Review 42 3.3 Analysis 45 3.4 Discussion 67 3.5 Implications and limitations 71 Chapter 4. The Effect of Communication Methods on Users Behavioral Changes in New media: Relationship between Game and Game-related content 74 4.1 Introduction 74 4.2 Research Framework and Hypothesis 77 4.3 Data and Results 85 4.4 Discussion & Conclusion 99 4.5 Implications & Limitations 104 Chapter 5. Does media usage lead to psychological distress The mediating effect of user participation on psychological well-being 106 5.1 Introduction 106 5.2 Literature Review and Research Question 110 5.3 Research Framework 114 5.4 Result 121 5.5 Implication 127 5.6 Conclusion & Limitation 131 Chapter 6. Discussion and Implications 133 6.1 Summary 133 6.2 Managerial Implication 137 6.3 Policy Implication 139 Chapter 7. Conclusion 141 Bibliography 144 Abstract (Korean) 177Docto

    A Meta-Analysis of the Relationship of Child-Abuse to Psycho-social Maladjustment:

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