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* This slide was made by Han Woo Park and his students to help Korean users use the NodeXL ์ƒˆ๋กœ์šด ๋„คํŠธ์›Œํฌ๋ถ„์„ ๋„๊ตฌ NodeXL ์ด ์Šฌ๋ผ์ด๋“œ๋Š” Marc Smith, Analyzing Social Media Networks with NodeXL์˜ 3,4์žฅ์„ ๊ธฐ์ดˆ๋กœ ํ•œ๊ตญ ์ด์šฉ์ž๋“ค์ด ๋…ธ๋“œ ์—‘์…€์„ ์‰ฝ๊ฒŒ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ๋งŒ๋“  ๋งค๋‰ด์–ผ์ž„.  ๋…ธ๋“œ์—‘์…€ ์ตœ๊ทผ ๋ฒ„์ „์„ ์‚ฌ์šฉํ–ˆ์œผ๋ฉฐ ์‚ฌ๋ก€ ๋˜ํ•œ ์›์ œ์™€ ์ƒ์ดํ•จ. ,[object Object],[object Object]
SNA ๋„๊ตฌ Social Network Analysis ๋Š” Social Network ๊ตฌ์กฐ, Social Media์™€ ๊ธฐํƒ€ Network ๊ตฌ์กฐ ๋“ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง€์›ํ•˜๋Š” ํˆด ์ฃผ์š” ๋„คํŠธ์›Œํฌ ๋ถ„์„ ํ”„๋กœ๊ทธ๋žจ์˜ ์ข…๋ฅ˜์™€ ๋น„๊ต  ์ถœ์ฒ˜: ๋ฐ•ํ•œ์šฐ(2010), LexiURL์„ ์ด์šฉํ•œ ๋™์‹œ๋งํฌ๋ถ„์„-์ •์น˜์›น์ง„,์ •์น˜ํฌ๋Ÿผ์‚ฌ์ดํŠธ, p.1098
์™œ ๋…ธ๋“œ์—‘์…€(NodeXL) ์ธ๊ฐ€ ?  ์ˆœํ™˜์  ๊ทธ๋ž˜ํ”„๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋ฅผ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ์กด์˜ ๋„๊ตฌ๋“ค์€ ๊ฐ๊ฐ ํ•œ๊ณ„๋ฅผ ๊ฐ€์กŒ๋‹ค. ๋„คํŠธ์›Œํฌ ๋ถ„์„์€ ํ•™์ˆ , ์ƒ์—…๊ณผ ์ธํ„ฐ๋„ท Social Media ๋“ฑ ๋ถ„์•ผ์—  ์ค‘์š”ํ•œ ์—ฐ๊ตฌ์˜์—ญ์ด๊ณ  ๋น ๋ฅธ ์„ฑ์žฅ์„ ๋ณด์ด๊ณ  ์žˆ๋‹ค. ํ˜„์žฌ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ๋˜ ๋„๊ตฌ๋Š” ๋ช…๋ น์„ ์ž…๋ ฅ ๋“ฑ์˜ ๋ฐฉ์‹์œผ๋กœ ๋„คํŠธ์›Œํฌ๋ฅผ  ๋ถ„์„ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋„๊ตฌ์— ๋Œ€ํ•œ ๋งŽ์€ ์ง€์‹์ด ํ•„์š”ํ•˜๋‹ค. ๋งŽ์€ ๋„คํŠธ์›Œํฌ ๋ฐ์ดํ„ฐ๋“ค์€ ExcelํŒŒ์ผ๋กœ ์ €์žฅํ•˜๊ณ  ์žˆ๋‹ค.
๊ฒฐ์ •์ ์œผ๋กœ Microsoft Excel 2007 ์ฐจํŠธ๊ธฐ๋Šฅ ์ค‘ ๋„คํŠธ์›Œํฌ ์ฐจํŠธ๊ฐ€ ์—†์Œ
NodeXL์˜ ์žฅ์    SNA(Social Network Analysis) ์‰ฝ๊ฒŒ ๋งŒ๋“ค์ž ๊ด‘๋ฒ”์œ„ํ•˜๊ฒŒ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋Š” Excel์— ๋„คํŠธ์›Œํฌ ๋ถ„์„ ํˆด์„ ๊ฒฐํ•ฉํ•˜์—ฌ  ์—ฐ๊ตฌ์˜ ์‹œ๋„ˆ์ง€ํšจ๊ณผ๋ฅผ ์‹คํ˜„ SNA ์ดˆ๋ณด์ž๋„  ์‰ฝ๊ฒŒ ์ ‘๊ทผํ•  ์ˆ˜ ์žˆ์Œ. NodeXL์€ ์•ž์„œ ๋‚˜์—ด๋œ SNA๋„๊ตฌ๋“ค์˜ ๊ฐ€์žฅ ๋ฐœ์ „๋˜๊ณ  ๊ฐ„ํŽธํ•œ ๋„๊ตฌ์ค‘์˜ ํ•˜๋‚˜๋ผ ํ•  ์ˆ˜ ์žˆ์Œ
NodeXL NodeXL๋Š” Microsoft Excel 2007์— ๋„คํŠธ์›Œํฌ ๋ถ„์„๋„๊ตฌ๋ฅผ ์ถ”๊ฐ€ํ•œ ์ƒˆ๋กœ์šด ๊ธฐ๋Šฅ ํˆด์ด๋‹ค. NodeXL๋Š” NET Framework 3.5 ์†Œ์Šค๋ฅผ ํ†ตํ•ด ๋‹ค๋ฅธ ๋„คํŠธ์›Œํฌ๋ถ„์„ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ์ด์šฉํ•œ ๋ถ„์„๊ฒฐ๊ณผ๋‚˜ ๊ธฐ์ดˆ๋ฐ์ดํ„ฐ๋„ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๋‹ค. NodeXL ๊ฐœ๋ฐœ์ž http://www.codeplex.com/NodeXL๋…ธ๋“œ์—‘์…€ ์‚ฌ์ดํŠธ์—์„œ ๋ฌด๋ฃŒ๋กœ NodeXL์ตœ์‹ ๋ฒ„์ „์„ ๋‹ค์šด๋กœ๋“œ๋ฐ›์„ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๊ฐ„๋‹จํ•œ ์‚ฌ์šฉ๋ฒ• ๋˜ํ•œ ๋ฐฐ์šธ ์ˆ˜ ์žˆ๋‹ค.
NodeXL๊ธฐ๋ณธ๊ตฌ์„ฑ
NodeXL๊ธฐ๋ณธ๊ตฌ์„ฑ NodeXL๋ฉ”๋‰ด์ฐฝ NodeXL๋„คํŠธ์›Œํฌ๊ทธ๋ž˜ํ”„  ํšจ๊ณผ์ฐฝ NodeXL๋ฐ์ดํ„ฐ ์ž…๋ ฅ์ฐฝ
NodeXL๊ธฐ๋ณธ๊ตฌ์„ฑ- ๋ฐ์ดํ„ฐ ์ž…๋ ฅ ์ฐฝ
NodeXL๊ธฐ๋ณธ๊ตฌ์„ฑ
 1. NodeXL์— ๋ฐ์ดํ„ฐ ๋งŒ๋“ค๊ธฐ and ๋ถˆ๋Ÿฌ์˜ค๊ธฐ Vertex1  ํ–‰์—์„œ Vertex2 ํ–‰์œผ๋กœ ํ–ฅํ•˜๋Š” ๋ฐ์ดํ„ฐ๋ฅผ ์ž‘์„ฑํ•œ๋‹ค. ๊ธฐ์กด์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถˆ๋Ÿฌ(import) ์˜จ๋‹ค. ํŠนํžˆ ๋…ธ๋“œ์—‘์…€์€Email, Flickr, Twitter, Youtube์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์žฅ์ ์ด ์žˆ๋‹ค.
๋งคํŠธ๋ฆญ์Šค๋กœ ๋‚˜ํƒ€๋‚ธ ๋„คํŠธ์›Œํฌ Edge list๋กœ ๋‚˜ํƒ€๋‚ธ ๋„คํŠธ์›Œํฌ ์œ„์˜ ๋‘ ๋งคํŠธ๋ฆญ์Šค์™€ Edge list๋Š”๋‹ค๋ฅด๊ฒŒ ํ‘œํ˜„๋œ ๊ฐ™์€ ๋„คํŠธ์›Œํฌ Edge list๋Š” Vertex1์—์„œ Vertex2๋กœ์˜ ๋ฐฉํ–ฅ์„ฑ์„ ๋‚˜ํƒ€๋ƒ„ ๋‹ค๋ฅธ ์†์„ฑ์„ ์ฒจ๊ฐ€ํ•˜์ง€ ์•Š๋Š”๋‹ค๋ฉด Vertex1์—์„œ vertex2 ๋กœ ํ–ฅํ•˜๋Š”(directed) ์ด์ง„๋ฒ•(binary)์ ์ธ ๋„คํŠธ์›Œํฌ๋ผ ํ•  ์ˆ˜ ์žˆ์Œ NodeXL์€ Edge list๋กœ ๋„คํŠธ์›Œํฌ๋กœ ๋ถ„์„ํ•จ ๋„คํŠธ์›Œํฌ ์ง€ํ‘œ๋“ค์€ ์ด์ง„(binary)๋งคํŠธ๋ฆญ์Šค์— ๊ธฐ์ดˆํ•ด ๊ณ„์‚ฐ ๋˜์ง€๋งŒ, Edge weight๋ฅผ ๋„ฃ์–ด์„œ ๊ด€๊ณ„์˜ ๊ฐ•๋„(valued)๋ฅผ ์‹œ๊ฐ์ ์œผ๋กœ ํ‘œํ˜„ ํ•  ์ˆ˜ ์žˆ์Œ
๋„คํŠธ์›Œํฌ๋ถ„์„์„ ํ•˜๋Š” Matrix ํŒŒ์ผ์„ edge list๋กœ ๋ฐ”๊พธ๊ธฐ 2 3 1 ๋…ธ๋“œ์—‘์…€ ์ฐฝ์— ๋งคํŠธ๋ฆญ์Šค ์‹œํŠธ๋ฅผ ํ•จ๊ป˜ ์—ด์–ด๋‘”๋‹ค ๊ธฐ์กด์˜ ๋„คํŠธ์›Œํฌ๋ถ„์„์„ ํ•˜๋Š” Matrix ํŒŒ์ผ์„ edge list๋กœ ๋‚˜ํƒ€๋‚ด์–ด ํ™œ์šฉ ํ•  ์ˆ˜์žˆ๋‹ค.
๊ด€๊ณ„๊ฐ€ ์žˆ๊ณ  ์—†๊ณ ๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” 2์ง„(binary)๋ฒ•์ , ๋ฐฉํ–ฅ์„ฑ์ด ์žˆ๋Š”(directed) ๋„คํŠธ์›Œํฌ ์™„์„ฑ.
๋…ธ๋“œ์—‘์…€์—์„œ ๊ฐœ์ฒด(vertices)๋Š” ์ƒ‰, ๋ชจ์–‘, ํฌ๊ธฐ, ํˆฌ๋ช…๋„์˜ ์„ฑ์งˆ๋กœ ํ‘œํ˜„๋  ์ˆ˜ ์žˆ๋‹ค
Autofill Columns์„ ์ด์šฉํ•˜์—ฌ  ์—ฐ๊ฒฐ์„ (Edge), ๊ฐœ์ฒด(vertex)์˜ ํฌ๊ธฐ์™€ ๊ฐ๊ฐ์˜ ์ค‘์‹ฌ๋„ ๋ฐ ํŠน์ • ๊ฐ’์— ๋”ฐ๋ผ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ๋‹ค.
2. NodeXL์„ ์ด์šฉํ•œ ๋„คํŠธ์›Œํฌ ๋ถ„์„  Graph Metrics ๋ฅผ์ด์šฉํ•˜์—ฌ ๊ฐ ๊ฐœ์ฒด๋“ค์˜ Degree, In-degree, Out Degree, Betweenness and Closeness centrality, Eigenvector centrality, PageRank, Clustering Coefficient, Group Metrics, ๋“ฑ์„ ๊ตฌํ•  ์ˆ˜ ์žˆ์Œ.
[object Object]
Betweenness Centralities: Bridge Scores for Boundary Spanners
Closeness Centrality: Distance Scores for Broadly Connected People
Eigenvector Centrality : Influence Scores for Strategically Connected People,[object Object]
NodeXL์‚ฌ๋ก€
NodeXL-์‚ฌ๋ก€  ์ฝ”๋ฉ˜ํŠธ ์ˆ˜์™€ ๋น„๋””์˜ค์˜ ์ˆœ์œ„์— ๋”ฐ๋ผ ๊ฐœ์ฒด์˜ ์ƒ‰๊ณผ ํฌ๊ธฐ๋ฅผ ๋‚˜ํƒ€๋‚ธ YouTube์˜ ๊ฑด๊ฐ•๋ณดํ—˜์— ๊ด€๋ จ๋œ ๋น„๋””์˜ค ๋„คํŠธ์›Œํฌ

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2016๋…„ ์ด›๋ถˆ์ง‘ํšŒ์˜ ํŽ˜์ด์Šค๋ถ ๋Œ“๊ธ€ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ๋ณธ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ฏธ๋””์–ด ํ˜„์ƒ
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2016๋…„ ์ด›๋ถˆ์ง‘ํšŒ์˜ ํŽ˜์ด์Šค๋ถ ๋Œ“๊ธ€ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ๋ณธ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ฏธ๋””์–ด ํ˜„์ƒHan Woo PARK
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Mais de Han Woo PARK (20)

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์†Œ์…œ ๋น…๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•œ_ํŽ˜์ด์Šค๋ถ_์ด์šฉ์ž๋“ค์˜_๋ฐ˜์‘๊ณผ_๊ด€๊ณ„_๋ถ„์„
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SNS ๋งค๊ฐœ ํ•™์Šต๊ณต๋™์ฒด์˜ ํ•™์Šต๋„คํŠธ์›Œํฌ ํƒ์ƒ‰ : ํŽ˜์ด์Šค๋ถ ๊ทธ๋ฃน์„ ์ค‘์‹ฌ์œผ๋กœ
SNS ๋งค๊ฐœ ํ•™์Šต๊ณต๋™์ฒด์˜ ํ•™์Šต๋„คํŠธ์›Œํฌ ํƒ์ƒ‰ : ํŽ˜์ด์Šค๋ถ ๊ทธ๋ฃน์„ ์ค‘์‹ฌ์œผ๋กœSNS ๋งค๊ฐœ ํ•™์Šต๊ณต๋™์ฒด์˜ ํ•™์Šต๋„คํŠธ์›Œํฌ ํƒ์ƒ‰ : ํŽ˜์ด์Šค๋ถ ๊ทธ๋ฃน์„ ์ค‘์‹ฌ์œผ๋กœ
SNS ๋งค๊ฐœ ํ•™์Šต๊ณต๋™์ฒด์˜ ํ•™์Šต๋„คํŠธ์›Œํฌ ํƒ์ƒ‰ : ํŽ˜์ด์Šค๋ถ ๊ทธ๋ฃน์„ ์ค‘์‹ฌ์œผ๋กœ
ย 
2016๋…„ ์ด›๋ถˆ์ง‘ํšŒ์˜ ํŽ˜์ด์Šค๋ถ ๋Œ“๊ธ€ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ๋ณธ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ฏธ๋””์–ด ํ˜„์ƒ
2016๋…„ ์ด›๋ถˆ์ง‘ํšŒ์˜ ํŽ˜์ด์Šค๋ถ ๋Œ“๊ธ€ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ๋ณธ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ฏธ๋””์–ด ํ˜„์ƒ2016๋…„ ์ด›๋ถˆ์ง‘ํšŒ์˜ ํŽ˜์ด์Šค๋ถ ๋Œ“๊ธ€ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ๋ณธ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ฏธ๋””์–ด ํ˜„์ƒ
2016๋…„ ์ด›๋ถˆ์ง‘ํšŒ์˜ ํŽ˜์ด์Šค๋ถ ๋Œ“๊ธ€ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ๋ณธ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ฏธ๋””์–ด ํ˜„์ƒ
ย 

Node xl korean_introduction

  • 1.
  • 2. SNA ๋„๊ตฌ Social Network Analysis ๋Š” Social Network ๊ตฌ์กฐ, Social Media์™€ ๊ธฐํƒ€ Network ๊ตฌ์กฐ ๋“ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง€์›ํ•˜๋Š” ํˆด ์ฃผ์š” ๋„คํŠธ์›Œํฌ ๋ถ„์„ ํ”„๋กœ๊ทธ๋žจ์˜ ์ข…๋ฅ˜์™€ ๋น„๊ต ์ถœ์ฒ˜: ๋ฐ•ํ•œ์šฐ(2010), LexiURL์„ ์ด์šฉํ•œ ๋™์‹œ๋งํฌ๋ถ„์„-์ •์น˜์›น์ง„,์ •์น˜ํฌ๋Ÿผ์‚ฌ์ดํŠธ, p.1098
  • 3. ์™œ ๋…ธ๋“œ์—‘์…€(NodeXL) ์ธ๊ฐ€ ? ์ˆœํ™˜์  ๊ทธ๋ž˜ํ”„๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋ฅผ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ์กด์˜ ๋„๊ตฌ๋“ค์€ ๊ฐ๊ฐ ํ•œ๊ณ„๋ฅผ ๊ฐ€์กŒ๋‹ค. ๋„คํŠธ์›Œํฌ ๋ถ„์„์€ ํ•™์ˆ , ์ƒ์—…๊ณผ ์ธํ„ฐ๋„ท Social Media ๋“ฑ ๋ถ„์•ผ์— ์ค‘์š”ํ•œ ์—ฐ๊ตฌ์˜์—ญ์ด๊ณ  ๋น ๋ฅธ ์„ฑ์žฅ์„ ๋ณด์ด๊ณ  ์žˆ๋‹ค. ํ˜„์žฌ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ๋˜ ๋„๊ตฌ๋Š” ๋ช…๋ น์„ ์ž…๋ ฅ ๋“ฑ์˜ ๋ฐฉ์‹์œผ๋กœ ๋„คํŠธ์›Œํฌ๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋„๊ตฌ์— ๋Œ€ํ•œ ๋งŽ์€ ์ง€์‹์ด ํ•„์š”ํ•˜๋‹ค. ๋งŽ์€ ๋„คํŠธ์›Œํฌ ๋ฐ์ดํ„ฐ๋“ค์€ ExcelํŒŒ์ผ๋กœ ์ €์žฅํ•˜๊ณ  ์žˆ๋‹ค.
  • 4. ๊ฒฐ์ •์ ์œผ๋กœ Microsoft Excel 2007 ์ฐจํŠธ๊ธฐ๋Šฅ ์ค‘ ๋„คํŠธ์›Œํฌ ์ฐจํŠธ๊ฐ€ ์—†์Œ
  • 5. NodeXL์˜ ์žฅ์  SNA(Social Network Analysis) ์‰ฝ๊ฒŒ ๋งŒ๋“ค์ž ๊ด‘๋ฒ”์œ„ํ•˜๊ฒŒ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋Š” Excel์— ๋„คํŠธ์›Œํฌ ๋ถ„์„ ํˆด์„ ๊ฒฐํ•ฉํ•˜์—ฌ ์—ฐ๊ตฌ์˜ ์‹œ๋„ˆ์ง€ํšจ๊ณผ๋ฅผ ์‹คํ˜„ SNA ์ดˆ๋ณด์ž๋„ ์‰ฝ๊ฒŒ ์ ‘๊ทผํ•  ์ˆ˜ ์žˆ์Œ. NodeXL์€ ์•ž์„œ ๋‚˜์—ด๋œ SNA๋„๊ตฌ๋“ค์˜ ๊ฐ€์žฅ ๋ฐœ์ „๋˜๊ณ  ๊ฐ„ํŽธํ•œ ๋„๊ตฌ์ค‘์˜ ํ•˜๋‚˜๋ผ ํ•  ์ˆ˜ ์žˆ์Œ
  • 6. NodeXL NodeXL๋Š” Microsoft Excel 2007์— ๋„คํŠธ์›Œํฌ ๋ถ„์„๋„๊ตฌ๋ฅผ ์ถ”๊ฐ€ํ•œ ์ƒˆ๋กœ์šด ๊ธฐ๋Šฅ ํˆด์ด๋‹ค. NodeXL๋Š” NET Framework 3.5 ์†Œ์Šค๋ฅผ ํ†ตํ•ด ๋‹ค๋ฅธ ๋„คํŠธ์›Œํฌ๋ถ„์„ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ์ด์šฉํ•œ ๋ถ„์„๊ฒฐ๊ณผ๋‚˜ ๊ธฐ์ดˆ๋ฐ์ดํ„ฐ๋„ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๋‹ค. NodeXL ๊ฐœ๋ฐœ์ž http://www.codeplex.com/NodeXL๋…ธ๋“œ์—‘์…€ ์‚ฌ์ดํŠธ์—์„œ ๋ฌด๋ฃŒ๋กœ NodeXL์ตœ์‹ ๋ฒ„์ „์„ ๋‹ค์šด๋กœ๋“œ๋ฐ›์„ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๊ฐ„๋‹จํ•œ ์‚ฌ์šฉ๋ฒ• ๋˜ํ•œ ๋ฐฐ์šธ ์ˆ˜ ์žˆ๋‹ค.
  • 11. 1. NodeXL์— ๋ฐ์ดํ„ฐ ๋งŒ๋“ค๊ธฐ and ๋ถˆ๋Ÿฌ์˜ค๊ธฐ Vertex1 ํ–‰์—์„œ Vertex2 ํ–‰์œผ๋กœ ํ–ฅํ•˜๋Š” ๋ฐ์ดํ„ฐ๋ฅผ ์ž‘์„ฑํ•œ๋‹ค. ๊ธฐ์กด์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถˆ๋Ÿฌ(import) ์˜จ๋‹ค. ํŠนํžˆ ๋…ธ๋“œ์—‘์…€์€Email, Flickr, Twitter, Youtube์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์žฅ์ ์ด ์žˆ๋‹ค.
  • 12. ๋งคํŠธ๋ฆญ์Šค๋กœ ๋‚˜ํƒ€๋‚ธ ๋„คํŠธ์›Œํฌ Edge list๋กœ ๋‚˜ํƒ€๋‚ธ ๋„คํŠธ์›Œํฌ ์œ„์˜ ๋‘ ๋งคํŠธ๋ฆญ์Šค์™€ Edge list๋Š”๋‹ค๋ฅด๊ฒŒ ํ‘œํ˜„๋œ ๊ฐ™์€ ๋„คํŠธ์›Œํฌ Edge list๋Š” Vertex1์—์„œ Vertex2๋กœ์˜ ๋ฐฉํ–ฅ์„ฑ์„ ๋‚˜ํƒ€๋ƒ„ ๋‹ค๋ฅธ ์†์„ฑ์„ ์ฒจ๊ฐ€ํ•˜์ง€ ์•Š๋Š”๋‹ค๋ฉด Vertex1์—์„œ vertex2 ๋กœ ํ–ฅํ•˜๋Š”(directed) ์ด์ง„๋ฒ•(binary)์ ์ธ ๋„คํŠธ์›Œํฌ๋ผ ํ•  ์ˆ˜ ์žˆ์Œ NodeXL์€ Edge list๋กœ ๋„คํŠธ์›Œํฌ๋กœ ๋ถ„์„ํ•จ ๋„คํŠธ์›Œํฌ ์ง€ํ‘œ๋“ค์€ ์ด์ง„(binary)๋งคํŠธ๋ฆญ์Šค์— ๊ธฐ์ดˆํ•ด ๊ณ„์‚ฐ ๋˜์ง€๋งŒ, Edge weight๋ฅผ ๋„ฃ์–ด์„œ ๊ด€๊ณ„์˜ ๊ฐ•๋„(valued)๋ฅผ ์‹œ๊ฐ์ ์œผ๋กœ ํ‘œํ˜„ ํ•  ์ˆ˜ ์žˆ์Œ
  • 13. ๋„คํŠธ์›Œํฌ๋ถ„์„์„ ํ•˜๋Š” Matrix ํŒŒ์ผ์„ edge list๋กœ ๋ฐ”๊พธ๊ธฐ 2 3 1 ๋…ธ๋“œ์—‘์…€ ์ฐฝ์— ๋งคํŠธ๋ฆญ์Šค ์‹œํŠธ๋ฅผ ํ•จ๊ป˜ ์—ด์–ด๋‘”๋‹ค ๊ธฐ์กด์˜ ๋„คํŠธ์›Œํฌ๋ถ„์„์„ ํ•˜๋Š” Matrix ํŒŒ์ผ์„ edge list๋กœ ๋‚˜ํƒ€๋‚ด์–ด ํ™œ์šฉ ํ•  ์ˆ˜์žˆ๋‹ค.
  • 14. ๊ด€๊ณ„๊ฐ€ ์žˆ๊ณ  ์—†๊ณ ๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” 2์ง„(binary)๋ฒ•์ , ๋ฐฉํ–ฅ์„ฑ์ด ์žˆ๋Š”(directed) ๋„คํŠธ์›Œํฌ ์™„์„ฑ.
  • 15. ๋…ธ๋“œ์—‘์…€์—์„œ ๊ฐœ์ฒด(vertices)๋Š” ์ƒ‰, ๋ชจ์–‘, ํฌ๊ธฐ, ํˆฌ๋ช…๋„์˜ ์„ฑ์งˆ๋กœ ํ‘œํ˜„๋  ์ˆ˜ ์žˆ๋‹ค
  • 16. Autofill Columns์„ ์ด์šฉํ•˜์—ฌ ์—ฐ๊ฒฐ์„ (Edge), ๊ฐœ์ฒด(vertex)์˜ ํฌ๊ธฐ์™€ ๊ฐ๊ฐ์˜ ์ค‘์‹ฌ๋„ ๋ฐ ํŠน์ • ๊ฐ’์— ๋”ฐ๋ผ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ๋‹ค.
  • 17. 2. NodeXL์„ ์ด์šฉํ•œ ๋„คํŠธ์›Œํฌ ๋ถ„์„ Graph Metrics ๋ฅผ์ด์šฉํ•˜์—ฌ ๊ฐ ๊ฐœ์ฒด๋“ค์˜ Degree, In-degree, Out Degree, Betweenness and Closeness centrality, Eigenvector centrality, PageRank, Clustering Coefficient, Group Metrics, ๋“ฑ์„ ๊ตฌํ•  ์ˆ˜ ์žˆ์Œ.
  • 18.
  • 19. Betweenness Centralities: Bridge Scores for Boundary Spanners
  • 20. Closeness Centrality: Distance Scores for Broadly Connected People
  • 21.
  • 23. NodeXL-์‚ฌ๋ก€ ์ฝ”๋ฉ˜ํŠธ ์ˆ˜์™€ ๋น„๋””์˜ค์˜ ์ˆœ์œ„์— ๋”ฐ๋ผ ๊ฐœ์ฒด์˜ ์ƒ‰๊ณผ ํฌ๊ธฐ๋ฅผ ๋‚˜ํƒ€๋‚ธ YouTube์˜ ๊ฑด๊ฐ•๋ณดํ—˜์— ๊ด€๋ จ๋œ ๋น„๋””์˜ค ๋„คํŠธ์›Œํฌ