online global communication(10 march2011)updating

인터넷과 국제(학술)정보- 하이퍼링크 네트워크 분석

박 한 우

영남대 언론정보학과 교수WCU 웹보메트릭스사업단장

영남대사이버감성연구소장아시아트리플헬릭스 디렉터

테드엑스팔공 디렉터

관련 사이트

http://www.hanpark.net http://webometrics.yu.ac.kr

http://asia-triplehelix.org

http://cerc.yu.ac.krhttp://tedxpalgong.com

http://www.hanpark.net/

http://english-webometrics.yu.ac.kr/

http://english-webometrics.yu.ac.kr/

http://asia-triplehelix.org/

http://asia-triplehelix.org/

http://cerc.yu.ac.kr/

http://tedxpalgong.com/

Defining community: Traditional

• Many concepts of community are rooted in sociologist Ferdinand Toennies’s concept of gemeinschaft

• Toennies distinguishes between gesellschaft, or society, and gemeinschaft, or community

• Gesellschaft is based on laws and other formal relations

• while gemeinschaft is the more spontaneous

relationships that develop based on physicality and customs and values

Defining community: Traditional

• The traditional definition of community has usually involved the geographic proximity of its members

• They live, work or socialize with each other,

therefore they are a community • Communities, ostensibly, are communities

of individuals, organizations, and countries that exist in physical space

• The development of digital technologies has helped lead to development of communities where members don’t have to be physically close to each other

• Shared (communicational, psychological, emo-tional) proximity

• A virtual society is built on the computer net-work, where people with a shared common in-terest can engage in the relationship of mutual communication that are not tightly tied to their geographic location

Cybercommunity: not geographically defined

Global cybercommunity

• No matter how great the distance between any two nodes, new digital technologies allow for communication at a low cost

• Such characteristics facilitate access to infor-mation on a global scale, making geographical distance fungible

• These have made the burgeoning world popu-lation in society increasingly interdependent in terms of social and communicational activities

글로벌리제이션

세계 각국의 국민들 사이의 사회적 관계가 강화되고 있는 현상은 글로벌화 과정을 정의하는 주요한 특징

국제 커뮤니케이션의 증가는 가치 , 아이디어 , 사상 , 기술의 전구적 확산 : 지구촌

새로운 정보 테크놀로지가 지리적 거리뿐만 아니라 사회적 , 심리적 , 문화적 거리를 상당부분 무의미하게 (fungible) 함으로써 개인간 , 그룹간 , 조직간 , 국가간 커뮤니케이션을 촉진

Globalization & Glocalization

• One of globalization’s characteristics is that our life has increasingly shifted from local sur-roundings to global relations

• Glocalization refers to the specific process in which a country rebalances the global and local identity

• Nation states aim at strengthening their social, cultural, economic, and academic sectors through building a regional block: EU, ASEAN, APEC, ASEM

글로벌 커뮤니케이션 채널로서 인터넷

• 인터넷은 공간적응형 (+ 비용절감형 ) 매체

• 두 사람 혹은 조직이 아무리 멀리 떨어져 있더라도 물리적인 거리의 장벽을 제거하고 즉각적인 (+ 저렴한 ) 커뮤니케이션을 허용

• 커뮤니케이션 파트너들 사이의 연결성을 향상시킴으로써 공간적 근접성을 변화

• 인터넷은 정보 확산을 위한 공간적 범위의 확장

International information flow• Past studies examine the structures, determin-

ants, and outcomes of the relational state among nation-states in terms of information flow

• Patents, citations, mass media, phone calls, softwares, trademarks, literature, recently hy-perlinks

Three major findings are:• Globalization is in progress• World system (core/periphery)• Imperialism (information rich/poor)

Research question

• But, the role and use of the Internet can be adjusted and determined at the particular geographical context

• One of controversial issues is whether the Internet facilitates or impedes the formation of global community (especially when compared to other existing technologies such as telephone)

• What is the relationship between the digital positions of individual nations and their physical locations?

• Internet flows among the 25 countries were measured in terms of hyperlink connectivity

• Unlike the telephone that devotes a single circuit to each individual message, the In-ternet is a packet switched network

• One alternative approach that allows the examination of international Internet flow is the analysis of inter-domain hyperlinks

Measuring Internet flows using hyperlinks?

Measuring Internet flows using hyperlinks?

• Hyperlinks can function as the paths of informa-tion flow, enabling one specific web domain to connect seamlessly with another

• Domains are sources of information in cy-berspace

• Domains serve as the origins and the destina-tions of online information flows

• Hyperlinks are a phatic communication device among Internet users allowing mutual recogni-tion

Universities’ sites are suitable?• Among many types of global websites, univer-

sities’ websites are a suitable sample for ex-amining the international distribution

• The universities are geographically located in each country and their websites are operated by people residing in a particular location

• For example, yahoo.com largely exists on cy-berspace although its registrar is based in the USA

Internet data• We selected the 2 university domains in each

country with the highest number of inlinks: the most web-visible universities

• AltaVista.com: host:sub-domain.source ccTLD AND link:sub-domain.target ccTLD

• The results of queries among universities were categorized by country, creating a 25 x 25 ma-trix

• The data were gathered for 2003

Distance data• Data on geographic distances among the 25

countries were based on the miles, as the crow flies, between the capitals of the countries

• This was calculated as the distances between the longitude and latitude measurement of the cities, using an online database at www.indo.com/distance

• The results of queries among countries were organized as a 25 x 25 distance matrix

http://www.indo.com/distance

사회 네트워크 분석의 시각

• 사회적 관계들이 사회적 존재들 ( 개인 , 그룹 , 조직 , 국가 ) 사이에 일어나는 교환행위에 따라 배열

• 교환내용은 상품 , 사회적 정체성 , 정보 등 가시적인 것부터 손에 잡히지 않는 것까지

• 커뮤니케이션 네트워크의 경우는 메시지 , 지식 , 혹은 정보가 사회 개체들간 교환되는 상호연결망 패턴에 초점

사회 네트워크 분석기법 : 중심성

• 연쇄연결 (eigenvector): 분석개체들간 관계가 이분적이 아니라 비교적 조밀한 관계

• 연결정도성 (degree): 관계의 방향을 고려

• 내향성 (indegree): 마치 외국에서 자국으로 관광객이 들어오는 것과 같이 , 어떤 개체가 다른 개체로부터 받은 관계의 빈도

• 외향성 (outdegree): 자국의 시민이 외국을 방문하는 것과 같이 어떤 개체가 주도하여 다른 개체와 맺는 관계의 빈도

그 외의 사회 네트워크 분석기법

• 집중도 (centralization): 중심적인 개체로 집중 정도 , 높을수록 한 개체에 집중되어 자원들이 불평등하게 배분된 상태

• 밀집도 (density): 통합성의 전반적 수준 , 구성원들간 실제 존재하는 관계의 수 / 가능한 관계의 수 [n(n-1)]

• 집락분석 (cluster analysis)• 다차원척도법 (MDS)• 매트릭스 상관관계법 (QAP)

http://participatorysociety.org/wiki/index.php?title=Online_Research




There does not exists a geographical barrier for information flow be-tween two continents Universities’ websites in Asia are heavily connected to European univer-sities rather than linked to each otherWhile Asia sends 8,219 links to Europe, the latter has only 3,506 links (42.7%) set up toward the former

Continent Asia EuropeAsia 2,364 8,219

Europe 3,506 47,648

Block modeling

Johnson’s Hierarchical ClusteringOverall, the clustering of link connec-

tivity pattern looks more like a ‘mitten’ rather than a ‘glove’

Specifically, links among universities’ websites in Asia are more ‘glove’-structured than in Europe

Geographical location does not neces-sarily have a big impact on communication on cyberspace

Clustering in Eurasia

Clustering in Europe

Clustering in Asia

Universities in Eurasia (at least 100 hyperlinks)

Euras ia As ia EuropeEuras ia Pearson r - 0.365

s ignifi cance 1.000As ia Pearson r 0.094

s ignifi cance 0.069Europe Pearson r - 0.293

s ignifi cance 0.003

QAP correlations

Physical distance is not the most impor-tant factor in the hyperlink connectivity structure

End of geography?!?!The results indicate that physical distance is not the most important factor in the link connectivity structure at global level

Which does not necessarily mean that geograph-ical location has no impact on computer-medi-ated communication at the local level !

Clear geographic trends are visible at national level, with most universities connecting mainly to other universities from the same country

Universities in Eurasia (at least 100 hyperlinks)

Universities in Europe(at least 100 hyperlinks)

Universities in Asia (at least 20 hyperlinks)

Universities in Asia (at least 50 hyperlinks)

Discussion issues• Role of geographical proximity needs to be studied

at various levels

• Hyperlinks as an indicator?

• Reliability of AltaVista.com

• Temporal process: a longitudinal research

• Physical distance in relation to other networks: Patents, citations, mass media, phone calls, software, trademarks, tourists, money, phone calls, migration, student exchange etc.

사이버 공간에서 지리적 거리의 역할

• 낙관론자 : 오프라인 공간의 언어 , 인종 , 재산 , 권력 , 거리의 구속과 제약을 넘어선 열린 커뮤니케이션 세상

• 언어 , 인프라 , 리터러시 , 법 / 제도의 차이

• 사이버 공간이 지리적 경계와 관계로부터 완전히 자유로운 공간 ? 충분히 검증 안됨

기존 관련 연구와 차별점

• 국가들 사이의 불평등한 정보흐름의 윤곽

• 정보제국주의에 대한 실증적 검토

• 전화에 기초한 국제 텔리컴 연구

• 인터넷에 기초한 선행연구의 경우 : OECD 에 소속된 25 개 선진국가만을 대상 , 2 차 데이터의 사용 , 지리적 거리를 주요 변수로 상정하지 않음

연구문제

• 사이버 공간에서 각 국가가 차지하는 디지털 위치는 무엇인가 ?

• 국가별 디지털 위치와 물리적 공간에서 국가간 지리적 거리는 어떤 연관성을 지니는가 ?

분석자료의 수집

• 47 개 국가들의 웹사이트 하이퍼링크를 AltaVista 를 이용해 수집

• domain: .kr AND link: .uk

• 검색엔진의 문제점이 적지 않으나 지속적으로 사용되며 , 신중한 해석 필요

• 분석국가들간 거리 데이터의 수집 : what-is-the-capital-of.com 과 INDO.com

연쇄연결성

1 USA 0.546 USA 15604977 Germany 210574612 UK 0.394 Indones ia 6854038 UK 131992223 Germany 0.296 India 6764779 USA 128701344 Aus tral i 0.293 Italy 4839254 USSR 54862705 India 0.206 France 4810245 Aus tral i 54263446 Canada 0.187 Norway 4071733 J apan 49033767 France 0.167 Austria 3818536 China 40397818 China 0.162 Malays ia 3662336 France 39027009 Italy 0.159 Iceland 3603710 Czech 3566929

10 Aus tria 0.141 Sweden 3158267 Italy 3449312

국가 외향성순위 국가 국가 내향성

순위 지역 내향성 값 지역 외향성 값1 중서유럽 4690093.6 북미 4823758.32 북미 4001716.5 중서유럽 3381892.23 동남아시아 2979472.3 오세아니아 30059014 북유럽 1689019.2 동북아시아 2555115.25 지중해연안 1386456.9 중동부유럽 1428147.46 동북아시아 902230.2 북유럽 989802.57 중동부유럽 871704.2 남미 717898.58 남미 783345.8 지중해연안 704421.39 오세아니아 641064.7 중동 32098910 중동 293291.7 아프리카 30744011 아프리카 146566.1 동남아시아 149595.8

합계 18384961 합계 18384961

MDS of intercontinental links

지리적 거리 평균값(average)

(sum)총값 내향값(indegree)

외향값(outdegree)

Pearson r - 0.068 - 0.068 - 0.087 - 0.009 p유의도 0.844 0.825 0.907 0.521

국가간 하이퍼링크의 빈도에 기초한 디지털 위치와 지리적 거리의 상관관계

디지털 위치 구조는 지리적 거리와 상관성이 부재

네티즌들은 물리적 거리에 크게 구애 받지 않고 다른 국가들 특히 , 중심적인 위치를 차지한 국가들을 자주 방문

요약 및 토론

• 미국을 선두로 , 영국 , 독일 , 호주가 중심적• 중서유럽과 북미가 중심적• 기존 정보제국주의 논의와 큰 맥락에서 일치

• 물리적 경계가 국가간 커뮤니케이션 빈도에 큰 영향을 미치는 않음을 보여주는 작은 단서

• 기존 연구결과와 유사 : NGO 네트워크는 지리적 위치보다 사업목표나 활동 , 정보통신 관련 조직들간 비즈니스 관계가 하이퍼링크 선택에 영향 , 멕시코 Zapatista 웹사이트

한계 및 제언

• 지리적 거리의 소멸 : 성급한 일반화 ?

• 국가를 분석단위로 하지 않은 연구들에서 , CMC 가 지리적 거리를 넘는 커뮤니케이션을 항상 촉진하는 것은 아니다 : 분석단위 다양화

• 하이퍼링크 분석은 growing & promising 그러나 검색엔진이 지닌 문제점을 극복해야

• 네트워크의 시계열적 분석

Research communication on the Web

• An informational and communicational turn within a research community since the intro-duction of new ICTs: Grid, database, e-journal, e-conference etc.

• More and more researchers are seeking to communicate via the Web, making their re-search information such as academic interests, research data, tools, or pre-prints available on their Web sites: online or invisible

Research question?

• How does an hyperlink network among research Web sites reflect off-line communication network among researchers?

• Specifically, this paper examines the similarities between the structure of the international hyper-linkage connectivity among universities’ Web sites belonging to the10 Asian countries and the pattern of co-authoring papers among researchers living in those countries.

Data gathering?

• Re-use of the already existing data• Co-authorship: Arunachalam & Doss (2000)

whose data were originally based on Science Cita-tion Index 1998.

• Hyperlink data: Thelwall & Smith (2002) whose data were originally gathered from AltaVista.com

• Their data sets were transformed to an (a)symmetrical 10 x 10 matrix for network analy-sis

Network analysis

• Bonacich centrality for symmetrical matrix• Degree centrality for asymmetrical hyperlink

matrix (in and out hyperlink)• Centralization for symmetrical matrix• Multidimensional scaling for symmetrical ma-

trix• Correlations between co-authorship and hyper-

link pattern: QAP, Pearson r

Result: Global centrality

• Co-authorship: China and Japan are the most cen-tral

• Hyperlink: instead of China, Japan and South Korea formed most cen-tral group

Co-authorship HyperlinkChina 0.603 0.180Japan 0.602 0.646S.Korea 0.359 0.517Taiwan 0.196 0.357Hong Kong 0.295 0.330Singapore 0.109 0.091Thailand 0.066 0.189Malaysia 0.033 0.018Indonesia 0.033 0.035Philippines 0.043 0.035

Result: Degree centrality

• Hyperlink: a big similarity between in and out r = .82

• While China is fairly peripheral in terms of out links, its position is simi-lar to S. Korea in terms of incoming links

Co-author OutDegree InDegreeChina 1436 1471 3209Japan 1474 11974 9251

S.Korea 635 7670 3828Taiwan 397 2655 6199

Hong Kong 549 4999 3827Singapore 237 1539 1083Thailand 145 648 3275Malaysia 96 213 337Indonesia 76 435 334

Philippines 95 317 578

Result: MDS of co-authorship

• At the center of the space are China and Japan

• S. Korea and Hong Kong are located near the origin of the space

Result: MDS of hyperlink

• A relatively tight grouping of Japan, S. Korea, Taiwan, and Hong Kong near the origin of the space.

• East to west, from the right to the left.

Results: Correlations

• A significant correlation between hyperlink and co-authorship (r = .57, p < .03)

• Co-authorship degree centrality showed a very similar relationship with both in (r = .70, p < .02) and out-link (r = .67, p < .02)

• Both the in and the out-link can be regarded as the indicator of hyperlink-mediated research communication

Discussion• Hyperlinks as communication networks?• What is more trustworthy? In or out link? Both?• Whether university Web sites represent research Web

sites or not?• The generalization of sample: 10 Asian countries• Temporal process• Relations with other networks: student flow • Impact of geography: not significant

Conclusion

• Hyperlink network analysis : interesting area, growing area, promising approach

• My other research: multi-mode research com-munications via email, IM, mobile etc.

• if you are interested in my work, [email protected]

• http://www.hanpark.net

Background: S. Korea and Taiwan are neither allied nor enemies?

• S. Korea and Taiwan: colonial rule of Japan, con-frontation with communist countries, economic growth, *cultural similarity? (inflow of S. Korean TV programs into Taiwan)

• however, S. Korea opened diplomatic relations with China in 1992, “one China” policy

• but two countries have to weigh the loss and bene-fits of further civic and economic cooperation (ex-port-oriented economy, can’t hurt to ask to main-tain an unofficial social tie)

Framework: International Informa-tion Flow Analyses (IIFA)

• IIFA is the study and interpretation of structures, determinants, and outcomes of the relational state among nation-states in terms of information flow: patents, data, citations, mass media, phone calls

• world system (core/periphery), imperialism (in-formation rich/poor), influence of information so-ciety technologies, role of national boundaries (g-lobalization/localization), impact of geography (cyberspace/physical distance)

International information flow inscribed on the Web

• Web facilitates access to information and knowl-edge on a global scale

• but, its role and use are adjusted and determined at the particular social context

• S.Korea and Taiwan may be a good case?• past research: we can discern fingerprints of inter-

national information flow based on configurations of hyperlink connectivity among Web pages that represent nation-states, and the analysis of contents exchanged via hyperlinks

Research question?

• what is the relational patterns of information ex-change from S.Korea to Taiwan on the Web based on hyperlinkage connectivity among Web pages that represent both countries?

• what influences the overall structures of hyperlink networks between two nation-states?

• what are the categories of hyperlink-mediated in-formation?, in other words, what are types of con-tents contained on hyperlinks?

Method: hyperlink networks

• hyperlink connectivity matrix, an m x n was made based on the results of AltaVista.com

• host:.ac.kr/ AND link:.edu.tw/• rows represent types of hyperlinking S. Korean pages

and columns, hyperlinked Taiwanese pages• m x n (i,j) is the number of S. Korean Web page i

which hyperlinked to Taiwanese page j • correspondence (network) analysis: the simultaneous

presentation of nodes both as initiators (rows) and receivers (columns)

Method: content analysis• systematic sampling• every 10th Web page (out of S. Korean pages) was se-

lected: N = 199• based on the author’s judgment, the types of informa-

tion contained on the page were classified according to the Yahoo taxonomy

• 14 classification schemes such as Business & Econ-omy, Computers & Internet, Society & Culture: not exclusive but rather illustrative

Result: hyperlink networks

• the number of S. Korean Web pages hyperlinking to Taiwanese pages was 1,994 out of 6,996,123 pages which ends with .kr (0.03%): very sparse connection

• S. Korean commercial pages (ending with .co.kr) provide the most hyperlinks to Taiwanese pages, 82.34% (1,039 out of 1,262) of their hyperlinking re-cipients are Taiwanese commercial pages

• other types of S. Korean pages such as academic and governmental pages showed similar patterns

Result: correspondence analysis

the closer, the more hy-perlinks outgoing hyperlink pat-terns of two different types of S. Korean pages are very simi-lar

Result: content analysis

• 88 out of the 199 sampled S. Korean Web pages (44.2%) conveyed the information about Computers & Internet. Business & Economy (31%) and News & Media (11.6%) followed

• compared to the high frequency of commercial infor-mation categories, academic and governmental cate-gories (such as Education, Government, Science, So-cial Science) occurred infrequently

• none of Arts & Humanities, Recreation & Sports

Discussion: hyperlink networks

• a relatively loose communication network from S. Ko-rea from Taiwan: generally consistent with past hyper-link and co-authorship research in Asia region

• S. Korean pages are more likely to hyperlink with simi-lar types of Taiwanese pages: S. Korean commercial, academic, and governmental pages send hyperlinks to their counter partner Taiwanese pages

• more than half of S. Korean pages (65.8%, 1,312 out of 1,994) are hyperlinking Taiwanese commercial pages

Discussion: content analysis• Computer & Internet category: Taiwan is one of top

five IT export countries of S. Korea, Export Similar-ity Index of S. Korea and Taiwan in the IT market of the USA is getting higher

• importance of IT trends in Taiwan as both S. Korean customers and competitors

• Taiwanese computer hardware, neither software nor dot-com companies: some aspects of industry

• News & Media: S. Korean’s interest in finding gen-eral information about Taiwan

Discussion

• hyperlinks as an indicator of international infor-mation and communication networks?

• only one way? AltaVista, a researcher’s language• expand to China (mainland) for comparison • how about whether both .kr and .tw Web sites rep-

resent each country or not?• temporal process: a longitudinal research• relations with other networks: mass media,

tourists, import/export, phone calls, migration, student etc.

Conclusion

• hyperlink network analysis : interesting area, growing area, promising approach

• my other research: multi-mode communications via email, IM, mobile in everyday life

• if you are interested in my work, [email protected] [email protected]

• http://www.niwi.knaw.nl/nerdi

• Exploring the contents of webpages between Korean and Chinese sites:

- Who are talking about what and how?

사이버 공간의 한국 - 중국 콘텐츠의 유형과 관계망

Background Korea and China are close to each other and the two peo-ples have similar cultural background and traditions.

Exchange activities between Korea and China can be traced back to the 6th century.

In 1992, South Korea and China re-established the official diplomatic relations, and communications between the peo-ple in both countries has started since then.

China was quickly become a major export market for Ko-rea.

Apart from economic activities, exchanges between the two countries have also included culture, entertainment, ed-ucation, science, to name a few.


Background

Year Korea to China China to Korea1997 584,487 214,2441998 484,009 210,6621999 820,120 316,6392000 1,033,250 442,7942001 1,297,746 482,2272002 1,722,128 539,4662003 1,569,245 512,7682004 2,334,781 627,2642005 2,963,162 710,2432006* - 896,969

The number of citizens’ visiting Korea and China

Data from Korea Tourism Organization *Began in July 2006 did not record travel destinations.


Background The speedy development of computer and internet tech-nologies have been seen as a cost-effective tool for pro-moting self images and reach more audiences around the world.

It is now possible for individuals and organizations to obtain and distribute information (on an unprecedented scale and at a low cost) and to form coalitions with like-minded groups in very short time scales.

A web site represent an individual, an organisation, and any other sort of entity. A web link to any pages on the Web represents recognition, acknowledgement, or a sugges-tion for example. Any changes on links might imply a change of affiliation, removal of relations, or disapproval.


Background

Research aims to study communications of Korean and Chinese citizens on the Internet.

The current structure of information flow between South Korea and China based on hyperlinking structures will be ex-amined.

Types of information communicated between South Ko-rean and China through the network structure will be inves-tigated.

Discuss some possible factors that might affect the cur-rent setting of the communciation environment between South Korea and China.


FrameworkGlobal networks are increasingly a part of our work and social life

today. Countries’ contact is not constrained by geographical restric-tions.

Global networks are not only tools but offer a venue for the global village, a matrix where the world can meet (Harasim,1993).

Data communications networks, such as the Internet, can create new opportunities for people to interact (Baym, 1993; Kraut et al, 1996; Rheingold, 1993).

International communication is the most common examples of commercial activities in the cyberspace.

The international communication is not only indicate on the field of economy but also include various things (e.g., scientific citations, broadcasting programs, data, telephone calls and e-mails.).


FrameworkInternational Information Flow Analyses (I-

IFA)

IIFA is the study and interpretation of structures, deter-minants, and outcomes of the relational state among na-tion-states in terms of information flow: patents, data, ci-tations, mass media, phone calls.

IIFA is the outcomes of the relational state among na-tion-states (Park, 2004), and to emphasize that interna-tional information flow has been maked as a main issue in the study of international communication (Barnett & Salis-bury, 1996; Barnett, 1999; Barnett et al., 2001).


FrameworkHyperlinking patterns in the Internet

Web studies of hyperlinking patterns in the Internet emerged in the mid-1990s.

Webometrics applies bibliometric and informetric tech-niques to investigate the Internet (Almind & Ingwersen 1997).

The major topics for Internet researchers include: structure of web links, web-based citation analysis, web impact factors and mapping (issue) networks.


FrameworkSocial Network Analysis (SNA) & Hyperlink Network Analysis (HNA)

SNA, which has been used to uncover patterns of interaction be-tween people, in particular “social and communication connections within a group”, can also be useful for disclosing virtual communica-tion patterns (Thelwall 2004).

SNA is now applied in many different fields of study, such as organ-isational behaviour, inter-organisational relations, social sup-port, the diffusion of information and political science.

Park (2003) referred to HNA, of which the idea was derived from communication studies (e.g., computer-mediated communication (CMC) networks). In a hyperlink network, actors are web sites (or nodes) belonging to individual, organisation, government, nation-state or others, and two individual nodes are connected by hyperlinks.


MethodHyperlink network analysis

LexiURL Searcher: A computer program designed to gather data from search engines via their applications programming interfaces (APIs) for webometric purposes, to retrieve data from the Yahoo! data base (Thelwall 2009).

Through LexiURL Searcher, we queried Yahoo! by submitting the command: linkdomain:.cn site:.kr and linkdomain:.kr site:.cn to search the hyperlinks between Korean website and Chinese website.

We used country code top-level domain (ccTLD) to search the links, not used top-level domain (TLD; e.g., .com, .net). It is the only and most nationally representative domain.


MethodSocial network analysis

The HNA mentioned earlier was derived from the social network analy-sis (SNA). This research also applies the basic concept and measure-ments of SNA. density: Which is an indicator of how connected the actors in a network are to one another. degree centrality: Which focuses on the number of neigh-bours an actor has. The more an actor connects directly to other network members, the more central the actor is.

Pajek was used to calculate some network metrics and NodeXL was employed to visualize Korea-China online networks.

Through these measurements, we are able to identify network pat-terns of these web pages and important web pages.


MethodContent analysis

LexiURL has ran-domly listed 400 web pages which link from China to South Korea and other 400 web pages from South Korea to China.


Results

KoreaChina

Korea to China 1. http://www.psdoctor.co.kr2. http://www.htclub.co.kr3. http://www.forklifts.co.kr 4. http://minge.pe.kr5. http://www.golf-fitness.co.kr6. http://www.kyung-shin.co.kr7. http://www.rootshell.co.kr Site 2326

Link 2505


ResultsChina to Korea Site 787Link 3971. http://www.nma.com.cn

2. http://www.takuya-openwiki.cn3.htttp://smkxxy.ntu.edu.cn4. http://en.syiae.edu.cn5. http://www.ec.cn6. http://www.xinli.sdu.edu.cn7. http://www.dongbanglfz.cn8. http://former.scnu.edu.cn

KoreaChina


Results Webpage compare중국에 링크한 한국 웹사이트의 도메인별 유형한국에 링크한 중국 웹사이트의 도메인별 유형Korea China

Domain Number % Domain Number %co.kr 243 60.8% com.cn 133 33.3%or.kr 45 11.3% edu.cn 29 7.3%ac.kr 42 10.5% org.cn 21 5.3%pe.kr 6 1.5% net.cn 15 3.8%re.kr 4 1.0% gov.cn 14 3.5%go.kr 3 0.8% ac.cn 12 3.0%


Results 중국에 링크한 한국 웹사이트의 생산자 및 포맷 유형한국에 링크한 중국 웹사이트의 생산자 및 포맷 유형Random webpage(400)-Korea vs. China

Author-Korea (297) Author-China (267)1. University 35 12% 1. University 24 9%2. Private company 249 84% 2. Private company 229 86%3. Government 3 1% 3. Government 9 3%4. Non-profit Organisation 5 2% 4. Non-profit Organisation 2 1%5. Personal 4 1% 5. Personal 3 1%6. Unknown 1 0%

Type-Korea (319) Type-China (334)1. Regular homepages 166 52% 1. Regular homepage 298 89%2. Blog 2 1% 2. Blog 9 3%3. BBS, message board, fo-rum (interactive) 149 47%

3. BBS, message board, forum (interactive) 24 7%

4. Document format 2 1% 4. Document format 3 1%


Results 중국에 링크한 한국 웹사이트의 주제분야별 유형한국에 링크한 중국 웹사이트의 주제분야별 유형Random webpage(400)-Korea vs. China

Content-Korea (177) Content-China (172)

1. Art & humanities 1 1% 1. Art & humanities 2 1%2. Business, economy, finance, industry 21 12%

2. Business, economy, finance, industry 37 22%

3. Trade 1 1% 3. Trade 12 7%

4. Education, academic, research 27 15% 4. Education, academic, research 39 23%

5. Entertainment 13 7% 5. Entertainment 15 9%

6. Health 11 6% 6. Health 2 1%

7. News & Media 14 8% 7. News & Media 4 2%

8. Recreation, sports, travel 18 10% 8. Recreation, sport, travel 10 6%

9. Religion 5 3% 9. Religion 1 1%

10. Science & technology 16 9% 10. Sience & technology 7 4%

11. Society 0 0% 11. Society 2 1%

12. Related links 30 17% 12. Related links 40 23%

13. Others 20 11% 13. Others 1 1%


Results

Author (132)University 9 6.82%Private Company 122 92.42%Government 1 0.76%

Content (82)Business, economy, finance, industry

53 64.63%

Education, aca-demic, research

5 6.10%

Health 13 15.85%News & Media 7 8.54%Recreation, sports, travel

1 1.22%

Science & Technol-ogy

3 3.66%

Type (136)Regular homepage 134 98.53%Blog 2 1.47%

Author (33)University 10 30.3%Private Company 20 60.6%Government 2 6.06%Non-profit Organ-isation

1 3.03%

Content (20)Business, econ-omy, finance, in-dustry

6 30%

Education, aca-demic, research

11 55%

Entertainment 2 10%Religion 1 5%

Type (37)Regular home-page

37 100%

한국의 target 이 된 중국 사이트의 유형 Korea to China

중국의 target 이 된 한국 사이트의 유형China to Korea


Discussions South Korea clearly has a stronger presence on the Inter-net: the network consists of more actors (2326 nodes, compared to787 nodes in the other network). It positively correlates with the offline situation that Korean people might have more interest in China.

Due to the country’s high broadband penetration, population distribution and government strategies (Kgoggin & MeLelland, 2009), South Korean citizens are highly engaged in online ac-tivities.

The popularity of Web 2.0 among Korean netizens also reflect on one of our findings that the majority of Chinese web pages are in the format of regular homepage (89%) while 52% of Korean web pages are regular homepages.

Social influence of the Internet is considered to play an important role in both countries.


Discussions The Chinese government is known for its attempt to exert control over the Internet. Government related factors that might affect the behavior of Chinese citizens in using more interactive func-tions of the Internet.

We assume that the use of the Internet in China might not be very different from other countries, as interactive technologies are used as a tool for communication and organisation.

One interesting finding is that one targeted Korean web page by the Chinese web sites belongs in our ‘religion’ class. Given the fact that in recent years the society has developed quickly and more opened to foreigners, people in China would receive more di-verse informaiton and start to use the Internet to search for more references.


LimitationOur research has shown that a social network based webometric analysis is a feasible methodology for studying web phenomenon.

Search engines do not cover all the data in the world wide web. In fact it is often suggested that commer-cial search engines only covers a fraction of the publicly available web.

We only used the 800 web pages randomly selected by Lex-iURL’s and the targeted web pages of these 800 pages to ex-amine what information has been communicated through the Internet. Thus, it is important to emphasize that our findings should not be overly generalized.


LimitationAnother limitation is related to the classification of web pages. Coders regarding content types of a web page is higher compared to ‘au-thorship’ and ‘web format’.

Some websites to be analyzed could not be opened or connected (e.g., termination of service, invalid website, website not found).

Some Chinese websites consist of a large number of uni-code and special symbols. We could not fully understand the content of information.

Some websites provide information related to a variety of topics. These website are difficult to distinguish in what cat-egory they should be placed.

Is global cyberspace becoming individualized or globalized?

Han Woo Park Department of Media and Information, WCU Webometrics Institute, YeungNam University, South Korea

[email protected]

George A. BarnettDepartment of Communication, University of California – Davis

[email protected]

Chung Joo ChungDepartment of Communication, State University of New York at Buffalo

[email protected]

mailto:[email protected]



Introduction

The widespread diffusion of the Internet & telecommunication networks

Global communication systems strengthen the worldwide social rela-tions and cultures are shaped and clustered across national borders (Barnett & Sung, 2006)

Few studies have examined the international Internet’s structure

An alternative approach is the analysis of inter-domain hyperlinks (Barnett, et al, 2001).

Web’s social structure as a technological link and communication net-work at the level of nation-states

Global Communication Networks The structure of int’l telecommunication (1) Increased centralization of communication flows

(Barnett et al., 1996; Barnett & Park, 2005; Chase-Dunn, 1989; Chase-Dunn & Grimes, 1995; Lee et al., 2007; Wallerstein, 1974)

rooted in a broader perspective of economics em-phasizing the asymmetry between countries

world-system theory (Barnett et al., 1996; Barnett & Park, 2005; Chase-Dunn, 1989; Chase-Dunn & Grimes, 1995; Lee et al., 2007; Wallerstein, 1974)

Literature Review and Re-lated Theories

(2) Increased diversification of communication flows (Barnett, 2001; Danowski, 2000; Lee et al., 2007; Matei, 2006; Monge & Matei, 2004; Robertson, 1992)

increasing trends of decentralization, regionalism or cultural pluralism

determination factors - countries’ geographical location (Barnett & Choi,

1995)- languages (Barnett & Choi, 1995)- religion (Barnett et al., 1999)- national culture (Barnett & Sung, 2006)


Longitudinal Approach Longitudinal studies with respect to the Internet are

difficult to conduct Some attempts to automatically index the changes

within a website over time Little research in examining the longitudinal hyperlink

structure generated by WWW on the international level

Did global cyberspace follow the main trend toward globalization and centralization of resources or be-come individualized and fragmented?


Research Questions

RQ1: What is the current (2009) structure of the international hyperlink network?

RQ2: How has the international hyperlink network changed between 2003 and 2009?

TLD Data Hyperlink connectivity between websites that

belong to ccTLD AltaVista and Yahoo were used respectively

for 2003 (Barnett & Park, 2005) and 2009 LexiURL Searcher

Automatic analysis of the impact of collections of web sites Link Impact Report

In the case of the U.S., three TLDs reserved for the exclusive use of American institutions, .edu, .gov, .mil were combined with .us

Methods- Data

The basic network data set an n x n matrix S, where n equals the number of

nodes in the analysis The basic network data set is an n x n matrix S,

where n equals the number of nodes in the analysis Each cell, Sij , indicates the strength of the relation-

ship among nodes i and j

Freeman’s degree centrality, Bonacich’s eigen-vector measure, hierarchical cluster analysis, MDS, Gini coefficient and QAP correlation and regression

Methods- Network analysis

Results

Table 1 International Hyperlink Centrality of the Top 30 Countries

Results

Figure 2. Incoming International Hyperlink Drawn using ManyEyes.com

Results

Figure 1. International Hyperlink Flow Network (2009)

Only those ties ex-hibiting greater than 1 million hyperlinks are shown. All isolates have been re-moved from the figure. N=251.

Results

Figure 3. International Hyperlink Structure in 2003

Only those ties exhibiting greater than 50,000 hyperlinks are shown (Barnett & Park, 2005). N= 47.

Results

Figure 4. International Hyperlink Structure in 2009

Only those ties exhibiting greater than 400,000 hyperlinks (eight times more compared to 2003, based on eight times degree difference) are shown. N=47.

Results

QAP Correlation & Regression The relation between the centrality of the

2003 and 2009 hyperlink networks of the 47 countries was significant (in-degree, r = .798, p < .01; out-degree, r = .815, p < .01; eigen-value, r = .821, p < .01).

The QAP correlation between the 2009 and 2003 data was only .406 (p < .01), account-ing for only approximately 16% of the vari-ance in the two networks.

Results

Some obvious and interesting changes The international hyperlink network became

more centralized over time. The composite score (Gini-based core/peripheral

measure) of the 2009 network was 0.466, whereas it was only 0.291 for the 2003 network.

The greatest changes were found among the most central countries.

Europe as a whole was much more central, particu-larly Germany.

The BRIC (Brazil, Russia, India and China) countries showed a number of changes.

The numbers of Brazil’s and Russia’s hyperlinks in-creased from 2003 to 2009.

China had fewer outward links. India had fewer inward links than expected.

Results

The centralities were distributed as a power curve (R2 ranging from .798 to .821) as Barabasi (2002) predicted, suggesting dispro-portional growth in the number of hyperlinks by the increased nodes (countries).

Whereas there was only one group in 2003, regional, cultural, and linguistic groupings formed in Latin America, Scandinavia, and around China and Russia in 2009.

Discussion

The structural position of a country is a result of its interactions with other countries

The structural position of a country determines its potential for development and its interaction patterns

The international hyperlink network became more centralized around G7 nations and Spain, with Western European countries joining the USA at the core.

Discussion

At the same time, regional clusters developed in what may be characterized as the semi-periph-ery.

Otherwise, the overall structure of the interna-tional hyperlink network remained relatively sta-ble.

Limitation

No indicators of the reliability of the measurement proce-dures or the validity of Yahoo’s search engine

Difficulties in addressing the nodes of Canada, Germany, and Indonesia, which share their domain names with var-ious U.S. states

.tv, Tuvalu’s domain name, is primarily used by the televi-sion (‘TV’) / entertainment industry

gTLDs such as .com, .net, .org or .eu websites need to be decomposed

Thank you for listening

If you want to cite this paper,

Park, H. W., Barnett, G. A., & Chung, C. J. (2011 forthcoming). Structural changes in the global hy-perlink network: Centralization or diversification. Global networks.

Available at http://www.hanpark.net

http://www.hanpark.net/

THANK YOU

online global communication(10 march2011)updating

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