After the emergence of Web 2.0, online art museums have been evolving into participatory museums, in an attempt to increase the public’s participation through the utilization of social media. Among many types of social media, social tagging has been receiving widespread attention as a tool for reducing the semantic gap between curators and visitors, through the group knowledge obtained from the active participation of the public.
In this circumstance, Gyeonggi Museum of Modern Art (GMOMA) embarked on an ongoing project with us to explore the potential of social tagging and applying it into museum management strategy. In the end of 2009, we built our own tag database based on the collections from GMOMA, and experiments were carried out by building a testbed on a website that was created to collect tags of 128 pieces of artworks.
After collecting the tags, we evaluated the feasibility of social tagging systems through workshops with curators from GMOMA. From the workshop we found the potentials of social tagging systems in museums through interviews and discussions with the curators, and identified the improvements that could be made in order to apply it to actual museums.
However, we discovered that while the number of tags increased, social tagging systems showed limitations in providing meaningful information and supporting semantic relationships between tags and museum collections.
The causes are as follows:
Lack of order, structure and depth in tags
Linguistic issues
Free forms of tags can cause ambiguity, chaos and noise
Spam tagsFailure to show the semantic relationships between tags; only provides an alphabetical list
Thus to achieve a participatory web and reflect the visitors’ semantic appreciation of museum collections, we conclude that the existing tagging systems should be supplemented. To improve the existing social tagging system and enhance the semantic appreciation in online art museum, our suggested solution is faceted tagging system which gives a guideline or schema to users when tagging the individual artworks. By collecting tags through the faceted tagging systems, we can automatically obtain a semantic structure and meaningful groups of tags. Before implementing the faceted tagging system and proving that it works, we had to make facets that cover the all the categories of art museum tags. We proceeded with card-sorting tests to extract and verify facets from the collected tag database. We retrieved six facets – “Background, Identification, Theme, Association, Emotion and Figure” – based on the semantic structure of tags, which were in a mess but now can be categorized into meaningful groups (facets).
Finally, user-tests are scheduled in order to prove that applying the six facets into the faceted tagging system can help to bridge the semantic gap between curators and audiences. For the user-tests, the same 128 artworks from the first experiment will be used, and we will compare the tags collected from the user-tests with the tags from the first experiment. Then we plan to discuss the feasibility of faceted tagging systems and its results – which we call structured tags – through a workshop with the curators from GMOMA.
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
MW2011: G. Chae +, Can Social Tagging Be a Tool to Reduce the Semantic Gap between Curators and Audiences?
1. Can Social Tagging Be a Tool to Reduce the Semantic Gap between Curators and Audiences? | KAIST GSCT | 2011.04.07 Chae, Gunho / Kim, Jungwha agarpe,jungwhakim@kaist.ac.kr KAIST, Republic of Korea Making a Semantic Structure of Tags by Implementing the Facetted Tagging System for Online Art Museums
2. “ Social tagging has been receiving widespread attention as a tool for creating new metadata on museum collections through the participation and knowledge of the public. ” (Trant and Bearman 2006; Smith, 2006; Chun, 2006; Chan 2007)
3. Social Tagging , Museum, Online Museum , Museum Website, Visitor-Oriented, Information Management , Social Computing, Tagging, Folksonomy , Web 2.0, Participation, constructivist Learning , Social Indexing , Accessibility, Museum Communication, Steve.Musuem, Online Collection, Social Search, Information Science, Art Museum, Meaning Making , social media
4. Gyeonggi Museum of Modern Art (GMoMA) and we started a new project for social tagging
5. Building a testbed for collecting social tags 10th ~28th of February, 2010 (19days) http://cultureplanning.kaist.ac.kr/socialtagging (based on steve-tagger 2.0) Results: No. of Artworks: 128 No. of Participants (Taggers): 168 No. of Tags: 14159
6. After the1st experiment, We organized workshops with GMoMA Curators (*1 st workshop: 15/04/2010) (*2 nd work shop: 28/04/2010) To find out what we gained from the experiment
7. Results from the experiment Light(6),Sunshine(5),Space(4),Loneliness(4),Sunlight(4),Empty(3),Room(3), Window(3),Angle(2),Calm(2),Lazy(2), Window with sunshine(2), Sunset(2),Composure(2),Afternoon(2),Chair(2),Working Room(2),cool(2) How can we interpret the tags from the audiece? What is their initial intention in tagging those words? … Tags Be gone, Boyeong jeong, Oil painting, 162*227.3, 2006
8. ? , 개미 , 거울 , 겨울 , 계곡 , 고독 , 골판지 , 공간 , 공포 , 공허 , 구름 , 국화 , 길 , 꽃 , 꿈 , 나무 , 나비 , 낚시 , 남극 , 누드 , 눈 , 단절 , 달 , 대비 , 대칭 , 도시 , 동양 , 동화 , 뒷모습 , 만화 , 모자이크 , 무서움 , 무제 , 무중력 , 바다 , 바람 , 반전 , 번짐 , 벚꽃 , 벽 , 병풍 , 봄 , 부조화 , 북한 , 빛 , 사과 , 사람 , 사진 , 산 , 산수화 , 새 , 선 , 선택 , 숫자 , 슬픔 , 시골 , 시원함 , 심오 , 심장 , 십장생 , 안개 , 액자 , 어머니 , 어지러움 , 엑박 , 여백 , 여성 , 여인 , 여자 , 여행 , 외로움 , 원 , 일본 , 자연 , 자유 , 자판기 , 전쟁 , 절벽 , 점 , 제사 , 조각 , 죽음 , 지도 , 징그러움 , 추상 , 타일 , 폐허 , 포도 , 폭포 , 풍경 , 피 , 핑크 , 하늘 , 합성 , 호수 , 혼란 , 홍수 , 환상 , 흑백 , 흙 Results from the experiment ? , 개미 ,Mirror,Winter, 계곡 , 고독 , 골판지 , 공간 ,Horror, 공허 ,Cloud, 국화 , Road , Flower , Dream , Tree , 나비 , 낚시 , 남극 ,Nude, Snow , 단절 ,Moon,Contrast, 대칭 ,City, 동양 ,Fairytale, 뒷모습 ,Cartoon,Mosaic, 무서움 ,nontitled, 무중력 , Sea , 바람 , 반전 , 번짐 , 벚꽃 , 벽 , 병풍 ,Spring, 부조화 , 북한 , Light ,Apple, 사람 , Photo , Mountatin , 산수화 , 새 , 선 , Choice , 숫자 ,Sorrow, 시골 , Cool , 심오 , Heart , 십장생 , 안개 , 액자 , Mother , 어지러움 , 엑박 , 여백 , 여성 , 여인 , Woman ,Travel, Lonley , 원 ,Japan, Nature , 자유 , 자판기 , War , 절벽 , 점 , 제사 , 조각 , Death , Map , 징그러움 , Abstract , 타일 , 폐허 , Grape , 폭포 , Scenary , 피 , 핑크 , Sky , 합성 , 호수 , 혼란 ,Flood, Fantasy , Black and White , 흙 What keywords can represent GMoMA’s collection? Why do they co-exist with each other? … Tag Clouds for the Top 100 Tags
9. But Certainly, we realize the power of social tagging in art museum…
10. “ So, GMoMA decided to apply social tagging system in their website” And we provide them new museum management strategies using social tagging system
11.
12.
13.
14. Chae, G. and Kim, J. (2011). “ Rethinking Museum Management by Exploring the Potential of Social Tagging Systems in Online Art Museums”. The International Journal of the Inclusive Museum, Vol. 3, Number 3, pp.131–140.
17. Still, We can’t help but wonder…. “ Can Social Tagging Be a Tool to Reduce the Semantic Gap between Curators and Audiences?” Our answer is “it needs more”.
19. Our suggesting solution is applying “ facetted tagging system” for art museum tagging system. A sample of Mefeedia’s Faceted Tagging interface (G. Smith 2008) What is “facetted tagging system”? The tagging interface at buzzillions.com gives two facets (G. Smith 2008) Facette | Facets for Delicious by Peter Lai, 2009
20.
21. Manual Indexing Research Process Literature Review 1. Constructing the Facet Structure Closed-Card Sorting Test Analyzing Artwork Description 2. Evaluating Feasibility of Facets Implementation Discussion 3. Implementing Facetted Tagging System
22. Black and White Mirror Winter Horror Cloud Road Flower Dream Tree Nude Snow Moon Contrast City Fairytale Cartoon Mosaic nontitled Sea Spring Light Apple Photo Mountain Choice Sorrow Cool Heart Mother Woman Travel Lonley Japan Nature War Death Map Abstract Grape Scenary Sky Flood Fantasy Manually matching each tags with artworks… And then trying to group them
23. Research Title Facets (or Classification) Results of Application Facet Tagging Inducing Ontology from Flickr Tags (Schmitz, 2006) Place, Activity, Depictions, Emotion, Response Place, Activity, Depictions, Emotion, Response Collaborative Classification of Growing Collections with Evolving Facets (Wu, 2007) Artifact, Location, Foreign Fairs, Topics, Year Location, Topics, Year Facetag: Integrating Bottom-up and Top-down Classification in a Social Tagging System (Quintarelli et al; 2007) Resource Types, Language, Themes, People, Purposes, Date People, Purposes, Date, Theme Tag Classification The structure of collaborative tagging systems (Golder and Huberman, 2005) Descriptive, Resource, Ownership/Source, Opinion, Self-reference, Task Organizing, Play and Performance Descriptive, Opinion Viewing Artwork Viewer tagging in art museums: Comparisons to concept and vocabularies of art museum visitors (Smith, 2006) Pictured people, Objects, Events, Actions, Simple mood, Emotions, Theme, Stories Pictured people, Objects, Events, Actions, Simple mood, Emotions, Theme The eye of the beholder: Measuring aesthetic development (Housen, 1983) Figure, Objects, Events, Story, Theme Figure, Objects, Events, Theme Facet Tagging Websites http://www.mefeedia.com Events, Language, People, Places, Topics Events, People, Places, Topics http://www.etsy.com (Ranganathan’s classicifacion) Space, Time, Material, Topic, Colors, Owners Space, Time, Material, Topic, Colors
24.
25. Black and White Mirror Winter Horror Cloud Road Flower Dream Tree Nude Snow Moon Contrast City Fairytale Cartoon Mosaic nontitled Sea Spring Light Apple Photo Mountain Choice Sorrow Cool Heart Mother Woman Travel Lonley Japan Nature War Death Map Abstract Grape Scenary Sky Flood Fantasy Manually matching each tags with artworks… And then grouping them into six groups Black and White Mirror Winter Horror Cloud Road Flower Dream Tree Nude Snow Moon Contrast City Fairytale Cartoon Mosaic nontitled Sea Spring Light Apple Photo Mountain Choice Sorrow Cool Heart Mother Woman Travel Lonley Japan Nature War Death Map Abstract Grape Scenary Sky Flood Fantasy Horror City Abstract Sorrow Death Cartoon Dream Cloud Background Identification Theme Association Emotion Figure
26. Manual Indexing Research Process Literature Review 1. Constructing the Facet Structure Closed-Card Sorting Test 2. Evaluating Feasibility of Facets 3. Implementing Facetted Tagging System
27.
28.
29. Manual Indexing Research Process Literature Review 1. Constructing the Facet Structure Closed-Card Sorting Test Analyzing Artwork Description 2. Evaluating Feasibility of Facets 3. Implementing Facetted Tagging System
30.
31. Result from Analyzing Artwork Descriptions SFMOMA IMA MOMA GUGGENHEIM Average Average number of facets implied in the artworks’ descriptions 4.6 4.3 4.8 5.8 4.9
32. Manual Indexing Research Process Literature Review 1. Constructing the Facet Structure Closed-Card Sorting Test Analyzing Artwork Description 2. Evaluating Feasibility of Facets Implementation 3. Implementing Facetted Tagging System
33.
34. Manual Indexing Research Process Literature Review 1. Constructing the Facet Structure Closed-Card Sorting Test Analyzing Artwork Description 2. Evaluating Feasibility of Facets Implementation Discussion 3. Implementing Facetted Tagging System
35. Idols on Narrative Stage, Hong Youngin, 2007 Result from the Implementation Social Tags Hero(4), Circus(3), Myth3), Collage(3), Satire (3), triumphal arch (2), Performance(2), Global(2), Flower(2), Rome(2), Stage(2), Temple(2), India(2), Parody(2), HongYoungIn(2), Dazzling(2) Facet tags Background Identification Theme Association Emotion Figure Greece(14) Statue(10) Hero(10) Mismatch(6) Unfocused(5) Collage(18) Ancient(14) God(9) Diversity(6) kitsch(5) Dignity(5) Photo(14) Medieval(12) General(6) Eastern and Western(5) Disturbance(5) insensibility(4) Magazine(7) Temple(10) Stage(6) Myth(5) Pop Art(4) Dazzling(4) Pop Art(7) Myth(7) Hero(6) Human(3) Greece(3) Inharmony(4) Paper(6) Modern(6) Flower(6) Chaos(3) Chaos(3) Fun(3) Canvas(4) Stage(6) Photo(4) Play(3) Dazzling(3) Gorgeous(3) Paints(2) Eastern and Western(5) Actor(4) Idol(2) Complex(3) Delight(2) Montage(2)
36. Non Titled, Lee Bul, Cast polyurethane paint, two-way mirror, wood frame, 160*120*13, 2008 Result from the Implementation Social Tags Machine(12), Infinity(4), Matrix(3), Handcuffs(3), Stocked(2), Mirror(2), Metal(2), Robot(2), Building(2), Cube(2), Transformer(2), Piano(2) Background Identification Theme Association Emotion Figure Future(25) Machine(26) City(9) 차가움 (6) 차가움 (16) 철 (12) Virtual Space(17) City(12) 차가움 (8) 특이함 (5) 무감각 (5) 컴퓨터그래픽 (11) 가상공간 (5) 건물 (9) 혼란 (6) 혼란 (5) 삭막함 (4) 그래픽 (8) 4 차원 (5) Robot(4) 혼돈 (4) 어두움 (3) 무서움 (3) 쇠 (6) 우주 (5) 철 (3) 미래 (4) 복잡함 (3) Coldness(2) 물감 (4) 현대 (4) 컴퓨터 (3) 불안 (3) 질서 (2) 딱딱함 (2) Metal(4) City(3) 아파트 (3) 어두움 (3) Computer(2) 메마름 (2) 종이 (4) Computer(3) Metal(3) 잿빛도시 (2) 도시화 (2) 폐쇄 (2) 플라스틱 (3) 겨울 (3) 기계장치 (3) 빨려들어감 (2) 멸망 (2) 두려움 (2) 컴퓨터 그래픽 (3) 사이버 (3) 미로 (2) 메마름 (2) Machine(2) 무감정 (2) 프린트 (2) 입체 (2) 건축 (2) 단단함 (2) 알수없음 (2) 혼란 (2) 액자 (2) 미로 (2) 톱니 (2) 현대문명 (2) Coldness(2) 답답함 (2) 사진 (2) Matrix(2) 알수없음 (2) 알수없음 (2) Future(2) 어지러움 (2) 컴퓨터 (2) world of dimensions(2) 설계 (2) 어두엄 (1) 삭막함 (2) 기이한 조합 (1) 디지털 프린트 (2) 그래픽 (2) 현실 (2) 보이지않는손 (1) Virtual Space(2) 낯선 감정 (1) 조형 (2) 5 차원 (2) 레고 (2) 롤러코스터 (1) Robot(2) 도발 (1) 알수없음 (2) 빛 (1) 인위적 (2) Virtual Space(1) 비인간화 (2) 경이 (1) 찹쌀떡 (1) virtual space(1) 액자 (2) 복잡함 (1) Matrix(2) 공허함 (1) 컴퓨터프로그래밍 (1)
37.
38. After the Implementation, Another workshop was held with GMoMA Curators (*workshop: 09/02/2011) For exploring potential of “ facetted tagging system” for art museums
39.
40. What can we expect by applying “ facetted tagging system” for art museums?
41. We can develop facet based collection browser! You can easily browse the artworks! Idols on Narrative Stage, Hong Youngin, 2007 Background Rome , Stage, Temple, India, Winter, Farm, NY, Seoul, War, River, Mountatin Theme Myth , triumphal arch , apple Hero, Satire, Stage, Circus, Global, Peace, Warmhearted, Love Emotion Satire, Dazzling, Horrified, Scary, Cold, Cool, Creepy, Cute, Sad Identification Hero, Flower, stage, triumphal arch, Global, Temple, coin, Pig, boy, red, Jeans, Time square Association triumphal arch, Performance, Stage, Myth, India, Hero,, Circus Global, Figure Circus, Collage, Parody, Performance, Contrast, Photo, Sculpture
42. Creating a new tagging interface And this can construct public-oriented collection metadata Idols on Narrative Stage, Hong Youngin, 2007 Background Rome , Stage, Temple, India Add Tags:_______________ Theme Myth , triumphal arch , Hero, Satire , Stage, Circus, Add Tags:_______________ Emotion Satire, Dazzling Add Tags:_______________ Identification Hero , Flower , stage, triumphal arch, Global, Temple, Add Tags:_______________ Association triumphal arch, Performance , Stage, Myth, India , Hero,, Circus Add Tags:_______________ Figure Circus, Collage, Parody, Performance Add Tags:_______________
Good After noon everyone I’m gunho and here’s my professor miss kim Today what I’m gonna talk is about social tagging, as you already knew. As you can see my tilts is Can Social Tagging Be a Tool to Reduce the Semantic Gap between Curators and Audiences? And subtitle is “ Making a Semantic Structure of Tags by Implementing the Facetted Tagging System for Online Art Museums “ You may guess this study suggest a new tagging system called facetted tagging for supplementing existing social tagging system in art museum For purpose of bridging the semantic gap between curators and audience So Here; we go
As see, first pioneerSteve.Museum which is leading research group who firstly adapt social tagging system into museum field And They starts this amazing project to collect tag for artmuseums And many museums for example indianapolis museum of art start tagging in their website
Since I met this research, I can’t help but to think about this new concept So Me and my professor starts to adapt social tagging in korean art museum. And we wanted to make use of social tagging as new museum management strategy So we started our research from 2009,
This is Gmoma, in short of Gyeonggi Museum of Modern Art . Gmoma is a leading korean national modern art museum. To research on tagging in art museum we wanted to show them the power of tagging so we firstly need to collect tags based on gmoma’ collection
So we used the steve tagger 2.0 and open the website. It was done from 10 th to 28 th of feburary. We used 128 artworks from GMOMA and 168 users participated tagging experiment For 19days we collected fourteen thousand and one hundred fifty-nine tags
After the1st experiment, We had workshops with GMoMA Curators for twice We showed them the tags we got from the public. And they we shocked and really like it. And they are getting acknowleged the power of tagging So we discussed with them, then how we can interpret those tags. And we asked a few questions for ourselves
This is the example of tags we got As you know sometimes or quite often its hard to inpterpret the tags. Why do they tag like that? What wast their intention? So, we had 2 questions. How can we interpret the tags from the audiece? What is their initial intention to tag that words?
And this is the tag clouds made of top 100 tags from the experiment Sorry they are all koreans, Except Question mark as you see there So I translated a few words. From now I translated quite many tags for your convenient, but as you know sometimes translation can be awkward. Pls understand this. From tag clouds the curators gmoma was quite shocked. They didn’t expect those keywords especially like “Mountain” “river” or “flowers… So once again we asked ourselve, What keywords can represent GMoMA’s collection? Why do they co-exist with each other?
Evethough we asked some questions to ourselves we checked the potential of social tagging. And finally gmoma decided to apply socialtagging system in their website In this decision making process, we consulted them and suggest some management strategies using social tagging system
Evethough we asked some questions to ourselves we checked the potential of social tagging. And finally gmoma decided to apply socialtagging system in their website In this decision making process, we consulted them and suggest some management strategies using social tagging system
And this research was our first outcome since we started tagging research Doing that research we can persuade a korean leading art museum to implement social tagging in their website. And we suggest a few museum management strategies for them
This is GMOMA’s old collection webpage As see, at the old one, every artworks page is showing like pop-up And it just shows the title, artist and some descriptions
However, this webpage went under construction to implement social tagging system So now every artwork has their own webpage and it has some social media features Now audience can participate in tagging activity
After reconstructing GMOMA website Still, We can’t help but wonder…. “ Can Social Tagging Be a Tool to Reduce the Semantic Gap between Curators and Audiences?” Our answer is “it needs more”. Though social tagging has a huge potential we still need to find answers for what we asked ourselve. As number of tags are increasing, We are surrounded by full of information, and so do tags Then How can we interpret the tags? And how to bridge the semantic gap between curators and audience?
We tried to research on related works in other social media research. Which already confront this kind of issues… They all present some limitations of existing social tagging system and tries to find their own solutions -> Emphasizing on Meaning, Structure and Facet (Classification)
So, Our Suggesting solution is applying “facetted tagging system” for art museum tagging system. Facets are more like categories within a metadata system. Each facet has a name and it addresses a different conceptual dimension or feature type relevant to the collection. Like this, ucc site, mefeedia using two facets – place and topic Buzzillion which is reviewing site gives also two facets – pros and cons about the product Next, Facette is a tool allows Delicious users to organize their bookmarks using facets. You can search delicious contents that facet browsing, also u can tag with facets like this
Then why art museum needs to use facet tagging system? For the Museum curators and Staffs Giving a chance to understand sematic structure of tags and tagger’s initial intention of tags Building public-oriented collection metadata based on facetted tagging For the Audiece structured tagging may be able to produce stronger user guidance , hence possibly resulting in higher quality descriptions. (Bar-Ilan et al. 2006) information seekers in large domains of objects prefer meaningful groupings of related items , in order to quickly understand relationships and so decide how to proceed (Hearst 2006)
So we start research again. We first wanted to create our own facet categories. And then evaluated the feasibility of facets. Lastly we implemented this facetted tagging system online and discussed its result And here’s the first. We used manual indexing to extract facets for artmuseums We used the tag DB we got from the first experiment and manually grouped based in similarity
This will help you understand how we construct facet First use top 100 tags and tried to group in by applying tags to each artworks And we made it into six groups Lastly we titled each groups “Background, Identification, Theme, Association, Emotion and Figure”
We referenced many fields iclude social media research, art appreciation, and some practical website And We found some facet candidate from the research And then Extracting facets that were applicable in viewing artwork, in this process we manually compare each tags and the facet candidate
For the last we compare the six facets we made and the literrature review And then Extrapolating six facets from the literature review
This will help you understand how we construct facet First use top 100 tags and tried to group in by applying tags to each artworks And we made it into six groups Lastly we titled each groups “Background, Identification, Theme, Association, Emotion and Figure”
The next step is evalutating the feasibility of facets We wanted to know the users can use this facet easily, so we sonduct card sorting test
We gave participants 6facets and approximately 20 to 30 tags to classify them into sic facets We gave them unlimited time, and then write the result using excel file 20 paticipants take part in this experiment and 10 art works are used
Here’s the results. We firstly checked Consistency of categorization between the participants: 91% of the Tags were classified into the 6 facets The pecentage of “More than 3 people categorized equally” is 61% The pecentage of “More than 2 people categorized equally” is 75% And the graph shows the percentage of portion that six facets have And the result give us confidence that our facet can reflect the user’s point of view
And then we moved to next step We also wondered do the six facet can also reflect the view of curators So we decided to analyze artwork descriptions based on 6 facets
This is one example how we analize the artwork descriptions We chose Ten artworks, from four museums’ website – SFMOMA, IMA, MOMA, and Guggenheim And then see analize them like this example
And the result shows that this 6 facets are used to descibe the artwork.. So we are quite confident of feasibility of our facets even from the curator’s vew So…..
We filany decided to implement this facetted tagging system
We created website which has faceted tagging interface. As you can see we give artwork and users can choose the facet and tag to each facet We used 24 artworks of gmoma This implementation took place for a week and 100users participated We collected 9400 tags and less than 2% of the total tags (165 tags) did not belong to any of the six facets and were classified as “etc”
영웅을 찾기도 하고 , 전체적인 느낌 속에서 영웅을 작푸이 가진 주제로 보기도 함 . 형태적으로 봣을때도 작품이 꼴라주이기에 안에 들어간 포토를 디픽 하기도 하고 , figure 로 보기도 함 POP Art 역시 작품 자체를 POP Art 로 보기도 하고 , 이를 보고 느끼기도 함
시대적 배경으로 Future 이며 동시에 이 작품에서 Future 를 Associate 하기도 함 City 의 경우 작품의 테마로도 , Spacial Background 로도 동시에 작품이 describe 하는 대상이 City 라고 생각하기도 함 또한 Metal 의 경우 작품의 Figure 라고 생각하면서 동시에 작품안에서 Describe 하는 대상으로 찾기도 함
작품의 주제와 연상 모두에서 Life 를 느낌 그리고 Creepy 의 경우 감정과 주제 , 연상 모두에서 등장함 또한 그림의 배경 색깔 때문인지 , 배경으로 그리고 연상으로 동시에 Sea 가 나온 것을 볼 수 있음 we are living in the generation surrounded by full of information, and so do tags Facet tags give us clues for interpreting the semantic structure of tags! We can guess the initial intention of taggers when they tag some words! It shows relation of tags by grouping them into facets!