WWW Hyperlink Networks

Transcription

1 WWW Hyperlink Networks Robert Ackland Australian Demographic and Social Research Institute (ADSRI) The Australian National University Notes prepared for Big Data Analysis for Social Scientists course ACSPRI Winter Program, Brisbane, 29 June 3 July 2015

2 Plan Approaches for modeling hyperlink networks: citation network issue network social network Comparison of the three approaches Ethics of hyperlink research 2

3 Modeling hyperlink networks (1): The web as a citation network 3

4 Webmetrics (or webometrics) is an example of informetrics - a subfield of information science involving use of mathematical-statistical approaches for analysis of communication in science. Four main areas: text content analysis, analysis of hyperlink structure, web usage analysis and web technology analysis Focus here on webometric contributions to hyperlink analysis 4

5 While webmetrics comprises many different techniques, a hallmark technique is the inlink count regression regress the number of inbound hyperlinks on attributes of the website and organisation/team running it Inlink count regressions focus on egonetworks, rather than complete networks typically only know attributes of ego, not alters 5

6 inlink count regression (webmetrics) 6

7 Barjak and Thelwall (2008) Evaluate the potential of hyperlinks as valid and reliable science and technology indicators regress counts of inbound hyperlinks to the websites of life science research teams on relevant offline characteristics of the teams (e.g. gender of team leader, industry connections, research productivity) Webometrics is mainly focused on explaining / characterising hyperlinking within academic web not clear that webometric techniques are as useful for studying other types of actors on the web e.g. advocacy groups (as will see, issue network and social network approaches more useful for studying these actors) Barjak and Thelwall also summarise stylised facts of academic hyperlinking 7

8 Academic hyperlinking stylised facts Information-related factors Many hyperlinks emanate from hubs (lists) and point to target pages or sites which carry actual information ( hub-authority nature of the web ) Large % of links are related to scholarly activity Quality of link data is reduced notably by noise The more information is included in a web document, the more links point to it The higher the quality (e.g. usefulness, credibility) of the information in a web document, more inlinks Quality is not absolute but relative, depending e.g. on the timeliness of the information or the availability of information on other sites. The longer a web page has maintained the same URL, the more inlinks it receives 8

9 Owner-related factors The higher the peer recognition of the page-owners (universities, departments), the higher the number of links to their web documents The higher the impact of the work of the page-owners (departmental level), the higher the number of links to their web presences Higher rated scholars do not produce web content with higher average impact, but they produce more content and hence gain a higher total impact Few hyperlinks represent communication or collaboration relations between the owners. Therefore, no clear relationship between the amount of collaboration and inlinks The influence of page owners demographic characteristics on inlinks is not confirmed 9

10 Environment-related factors The number of links differs between scientific disciplines and research fields Link patterns (e.g. sources of inlinks) differ between disciplines The number of links differs between countries The larger the distance between two universities the fewer the number of links that connects them 10

11 Tools Mike Thelwall (Univ. of Wolverhampton) is a key person in webometrics Has developed tools for webometrics SocSciBot ( a Web crawler for link analysis research. It is for link analysis on a single web site or collection of sites, or for text search/analysis on a collection of sites. SocSciBot (a) crawls one or more web sites and (b) analyses them to produce standard statistics about the interlinking and network diagrams of the interlinking. It also runs limited analyses of the text in the web sites. 11

12 Webometric Analyst (formerly known as LexiURL Searcher) a program to conduct automatic analyses of the impact of collections of documents or web sites, or to create network diagrams of collections of web sites. It has the ability to automatically submit queries to search engines and process the results. Main features: Web Impact Report of the number of times each of a set of words, phrases or documents have been mentioned online Link Impact Report of the number of web pages and web sites that link to one or more web sites or web pages Web Environment Network of an individual web site Network diagram of the links between a collection of web sites 12

13 Modeling hyperlink networks (2): The web as an issue network 13

14 The concept of the issue network is primarily associated with Richard Rogers who has developed the Issuecrawler (web-based software for constructing and analysing issue networks) Issue networks emerge when actors pursuing a common goal generate an associational space, defined by hyperlinks. When we took to the web to study public debates we [found] issue networks instead (Marres 05) Notions of the Web as public debate space, with the virtual roundtable construct did not fit with the empirical findings. Richard Rogers Rogers says we can distinguish issue networks from popular understandings of networks: Actors may not be on the same side of an issue. Actors may be organisations, individuals, news stories, leaks etc Actors may be antagonistic, adversarial, 14 estranged

15 Modeling hyperlink networks (3): The web as a social network 15

16 Relational hyperlink analysis Lusher and Ackland (2009) Main contribution of paper is methodological propose relational hyperlink analysis (RHA) ERGM applied to hyperlink network - as a distinct approach for social science hyperlink research Compared with commonly-used hyperlink counts regression approach (hallmark of webmetrics), RHA can lead to different conclusions about the social processes underpinning hyperlinking behavior. counts regressions may over-estimate the role of actor attributes in the formation of hyperlinks when endogenous, purely structural network effects are not taken into account. 16

17 For certain types of actors on the web, it is appropriate to study hyperlink network as social network What types of actors? Where we can expect high level of informal/endogenous tie formation i.e. social- versus institutional- linking. Links occur for social reasons (e.g. reciprocity, transitivity) as well as reasons relating to actor attributes 17

18 One would not study academic hyperlinks as a social network for two reasons: as we saw earlier, hyperlinks are not good indicators of academic communication/collaboration...to the extent that this communication/collaboration may involve social behaviour, probably not reflected in hyperlinks academic hyperlinks are akin to citations, and two main theoretical models of citation behaviour do not involve citations being formed for structural or endogenous reasons (they instead emphasise actor-relation effects): citation as a normative process - recognize academic debt to authoritative and relevant prior work. social constructivists disagree that academics follow internally sanctioned norms. Citations are mainly rhetorical tools of persuasion whereby authors attempt to buttress their arguments by making citations that are not based on academic merit or relevance, but because of the position or rank of the cited author in the field of research. 18

19 What does it mean to study a hyperlink network as a social network? Data preparation. Emphasis on three related factors: what are the nodes? what are the social ties? what are the boundaries to the network? Generally this is determined by the above two questions. Analytical technique: ERGM 19

20 144 refugee and advocacy websites classified into three groups Lobby groups produce media releases and submissions to government Service providers provide legal, health, counseling, food etc. to asylum seekers/refugees Research groups conduct research into asylum seekers/refugees 20

21 RAS hyperlink network sorted vertically by indegree (red nodes are lobby sites) 21

22 FDG of RAS hyperlink network (red nodes are lobby sites) 22

23 Hypothesis proposed by Lusher and Ackland (2009) is simple: that RAS advocacy online network participants are more likely to hyperlink to lobby sites since this will increase traffic to these sites (and hence allow them, via petitions, to more effectively lobby government). Figures and Model A (ERGM where no purely-structural effects included) appear to support this red nodes appear more prominent in figures in Model A significant and positive receiver effect for lobby sites But in Model B (purely-structural effects included), no significant receiver effect for lobby sites 23

24 Conclusion Advocacy actors engage in informal networking behaviour i.e. their hyperlink networks have features of social networks - purely structural network effects such as transitivity and reciprocity if don't take account of this in the modelling strategy ERGM including purely structural effects then might get spurious actor-relation effects i.e. mistakenly conclude that lobby sites are receiving more hyperlinks RHA is appropriate technique for studying these types of actors (but not necessarily other types e.g. government agencies) 24

25 Ackland and O Neil (2011) analyse hyperlinks and online collective identity, focusing on environmental activist websites Websites were categorised according to the main issues or causes (bio, toxics, globals) While some geographical information was also used in the analysis (websites were categorised according whether the organisation is located in the geo-political north or south), the primary focus was on information about sub-movement identity information that could be garnered directly from the Web, rather than offline characteristics. 25

26 In contrast, Gonzalez-Bailon (2009) focused on offline-attributes of NGOs Modeled the hyperlink network of 967 NGO websites and found that offline economic resources (proxied by number of paid staff) and visibility (proxied by LexisNexis archive data on total number of mentions in major world publications, newspapers,tv and radio) has a significant impact on the probability of receiving hyperlinks (using the ERGM terminology, there are significant receiver effects for offline economic resources and visibility). The results led to a conclusion that...some agents enter the web from a position of strength that does not derive from their online activities but from their access to economic resources and offline visibility Gonzalez-Bailon (2009, p.279) 26

27 Identifying a hyperlink network 27

28 Identifying a hyperlink network Laumann et al. (1983): the definition of a social network involves three fundamental and interrelated issues: (1) What constitutes a social tie? (2) Who are the nodes/actors? and (3) Where is the network boundary?. These three questions can help to clarify the differences between the three disciplinary approaches to studying hyperlink networks. 28

29 Who are the nodes? For citation hyperlink networks and social hyperlink networks, the nodes are typically websites that represent groups/organizations (that may or may not have an offline presence) or individuals (e.g. blogs). With issue networks the nodes can represent objects (e.g. news items, documents) that are relevant to the issue being studied. 29

30 What constitutes a tie? Digital trace data: interpretation of hyperlink? Hyperlinks in citation/social hyperlink networks typically indicate positive, rather than negative affect relations i.e. transfer of symbolic or practical resources that recipient wants to receive. Barjak and Thelwall (2008) - hyperlinks to academic project websites convey practical resources in the form of intellectual authority, status or prominence. Ackland and O'Neil (2011) hyperlinks between environmental activist websites convey both practical resources ( index authority ) and symbolic resources or boundaries of belonging, which help to establish online collective identity. In citation/social hyperlink networks, actors less likely to link to dismiss 30

31 Citation hyperlink network Expected to exhibit only actor-relation effects Social hyperlink network Expect to exhibit both actor-relation effects and endogenous/structural network effects Issue network Can expect existence of negative affect relations Because issue networks can contain objects (news items, documents) hard to conceive of issue network containing network effects (and amenable to being modeled using ERGM). 31

32 Network boundaries / selection of nodes For citation hyperlink networks may be possible to identify population of relevant websites e.g. Barjak and Thelwall (2008) identified all European-based biotech research teams May conduct a census or draw a random sample With an issue network and social hyperlink networks, underlying population often cannot be identified in advance and a snowball sampling approach is needed to draw additional nodes into the network. 32

33 Network type Network type is also useful for distinguishing disciplinary variants of hyperlink network research. Types of networks: Ego network (personal network) focal node ( ego ) directly connecting to alters (1-degree, 1.5 degree, 2 degree variants). Complete networks contain all nodes and all connections 33

34 Example: studying climate change Citation hyperlink network: Identify set of environmental activist sites that are involved in the climate change debate. Find count of inbound hyperlinks to each site i.e. 1-degree ego network for each site. No information on how egos connect to one another. No information on the connections between the alters. Effectively reducing link structure to counts of inbound links to egos. Social hyperlink network: Construct the complete network for the set of environmental activist sites. Issue network: Also a complete network, but includes nodes other than the environmental activists e.g government/business 34

35 Ethics of hyperlink analysis 35

36 Ethics of hyperlink analysis Data on people is used without their approval, and possibly for purposes they might not agree with What are the ethical considerations? Documents can be researched without approval, but people can t. Web pages/facebook profiles etc. are just documents (HTML), so does that mean we can conduct this research without permission? When should anonymity be granted to research subjects (page owners)? When a possibly undesired label may be attached to the person or group (e.g., hate group, terrorist) When naming the individual/organisation might lead to undesirable effect (e.g., league table ranking of hate sites) When publicly private individual is singled out (e.g., detailed analysis of an average blogger or FB participant) 36

37 There are particular ethical issues associated with the use of webcrawlers for research (Thelwall and Stuart, 2006). First, crawling a website can potentially use a lot of the resources (e.g. bandwidth, CPU time) of the website owner, which could lead to significant costs or loss of service quality. For this reason it is important that webcrawlers are used responsibly, for example by not crawling the sites of organisations who might be resource constrained (e.g. NGOs in developing countries), and also by limiting the crawler so there are delays between each page request. Second, it is important that webcrawlers obey the robots.txt protocol, which is used by webmasters to inform crawlers which parts of the website can be crawled and which parts are off limits. 37