Link analysis: an information science approach
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam [u.a.]
Elsevier
2004
|
| Schriftenreihe: | Library and information science
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XII, 269 S. graph. Darst. |
| ISBN: | 0120885530 |
Internformat
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Datensatz im Suchindex
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|---|---|
| adam_text | Introduction v
Link Analysis: An Information Science Approach
PartI: Theory 1
1 1
Introduction 1
Objectives 1
Link analysis 1
Historical overview 2
What is the information science approach to link analysis? 3
Contents andstructure 4
Key terminology 5
Sumtnary 6
Further reading 6
References 7
2 9
Web crawlers and search engines 9
Objectives 9
Introduction 9
Web crawlers 9
Findingpages 11
Content crawling vs. URL crawling 11
Content crawling 14
Obscured links 14
Depth and other arbitrary limitations 15
Automatically generated pages 15
Ethical issues and robots.txt 17
The webpage 17
Web crawling summary 18
Search engines 18
Knownbiases 19
Search engine ranking 20
The Internet Archive 20
Summary 20
Further reading 21
References 21
3 23
The theoretical perspective for link counting 23
Objectives 23
Introduction 23
The theoretical perspective for link counting 23
Anomalies 24
Manual filtering and banned lists 26
Alternative Document Models 27
Web sites and web documents 27
ADMs and Standard ADM counting 29
ADM ränge counting modeis 30
Choosing link counting strategies 31
vi Link Analysis: An Information Science Approach
Summary 32
Further reading 32
References 33
4 35
Interpreting linkcounts: Random samples and correlations 35
Objectives 35
Introduction 35
Interpreting link counts 35
The pilot feasibility and validity study 37
Full scale random sampling 38
Confidence limits for categories 40
Correlation testing 41
Literature review 43
Summary 43
Further reading 43
References 44
Part II: web structure 47
5 47
Link structures in the web graph 47
Objectives 47
Introduction 47
Power laws in the web 48
Models of web growth 50
Link topologies 52
Power laws and link topologies in academic webs 54
Summary 55
Further reading 56
References 56
6 59
The content structure of the web 59
Objectives 59
Introduction 59
The topic structure of the web 60
A link content web growth model 61
Linktext 62
The subject structure of academic webs 62
Colinks 66
Summary 66
Further reading 67
References 67
III Academic links 69
7 69
Universities: Link types 69
Objectives 69
Introduction 69
Citation analysis 69
The role of a university web site 70
Introduction vii
National Systems of university web sites 71
Page types 72
Link types 75
Summary 77
Further reading 78
References 78
8 81
Universities: Link modeis 81
Objectives 81
Introduction 81
The relationship between inlinks andresearch 81
Academic linking: Quality vs. quantity 84
Alternative logical linking modeis 86
Mathematical modeis 87
The influence of geography 88
Regional groupings 89
Summary 91
References 91
9 93
Universities: International links 93
Objectives 93
Introduction 93
National vs. international links 94
International linking comparisons 95
Linguistic influences 96
Summary 98
Further reading 99
References 99
10 101
Departments and subjects 101
Objectives 101
Introduction 101
Departmental web sites 102
Disciplinary differences in link types 103
issues of scale and correlation tests 104
Country 105
Subject 105
Outcome 105
Geographie and international factors 106
Summary 106
Further reading 107
References 107
11 109
Journals andarticles 109
Objectives 109
Introduction 109
Journal Impact Factors 109
Journal web sites 110
viii Link Analysis: An Information Science Approach
Journal web site inlinks: Issues 111
Journal web site inlinks: Casestudy 112
Types of links in Journal articles 113
Digital library links 114
Combined link and log file analysis 114
Related research topics 115
Summary 116
Further reading 116
References 116
IV Applications 119
12 119
Search engines and web design 119
Objectives 119
Introduction 119
Link structures and crawler coverage 119
Text in web sites and the Vector Space Model 120
The PageRank algorithm 121
Case study: PageRank calculations for a gateway site 124
HITS 127
HITS worked example 128
Summary: Web site design for PageRank and HITS 131
Further reading 132
Appendix: the Vector Space Model 133
References 134
13 137
A health check for Spanish universities 137
objective 137
Introduction 137
Research questions 137
Methods 138
Results and discussion 138
Conclusion 144
References 144
14 145
Personal web pages linking to universities 145
Objectives 145
Introduction 145
Web publishing and personal home pages 146
Research questions 147
Methods 148
Data collection 148
Data analysis 149
Results 151
ISPbiastest 151
ADMfming 152
Correlations between links and research ratings 153
A comparison of university and home page link sources 154
Introduction ix
Individual page categorizations 155
Conclusion 158
Meta conclusions 159
Acknowedgement 159
References 160
15 163
Academic networks 163
Objectives 163
Introduction 163
Methods 163
University Sitemaps 164
National academic web maps 168
Subject maps 170
Summary 171
Further reading 171
References 172
16 173
Business web sites 173
Objectives 173
Introduction 173
Site coverage checks 173
Site indexing and ranking checks 174
Competitive intelligence 174
Casestudy 175
Center Parcs 176
Hoseasons 176
Butlins 177
Pontins 178
Haven Holidays 178
General queries 179
Summary 179
Further reading 180
References 180
V Tools and techniques 181
17 181
Using commercial search engines and the Internet Archive 181
Objectives 181
Introduction 181
Checking results 182
Dealing with variations in results 183
Using multiple search engines 184
Using the Internet Archive 184
Summary 185
Online resources 185
Further reading 186
References 186
18 189
Personal crawlers 189
x Link Analysis: An Information Science Approach
Objectives 189
Introduction 189
Types of personal crawler 189
SocSciBot 190
Web page retrieved 190
Web page qualification 191
Web link extraction 192
URLs from HTTP 192
Obscured or unspecified URLs 193
Server generated pages 193
Dealing with errors 194
Human Intervention during crawls 195
SocSciBot tools 195
Summary 196
Online resources 196
Further reading 196
References 197
19 199
Data cleansing 199
Objectives 199
Introduction 199
Overview of data cleansing techniques 199
Anomaly identification 200
TLD Spectral Analysis 201
Summary 201
Online resources 202
References 202
20 203
Online university link databases 203
Objective 203
Introduction 203
Overview of the link databases 203
Link structure files 204
The banned lists 205
Analyzing the data 206
Other link structure databases 206
Summary 206
Online resources 206
Further reading 206
Reference 208
21 209
Embedded link analysis methodologies 209
Objectives 209
Introduction 209
Web Sphere Analysis 210
Virtual ethnography 210
Summary 211
Introduction xi
Further reading 212
References 212
22 213
Social Network Analysis 213
Objectives 213
Introduction 213
Some SNA metrics 214
Software 215
Summary 216
Further reading 216
References 216
23 219
Network visualizations 219
Objectives 219
Introduction 219
Network diagrams 219
Large network diagrams 221
MultiDimensional Scaling 221
Self Organizing Maps 222
Knowledge Domain Visualisation 223
Summary 223
Online resources 223
References 223
24 227
Academic link indicators 227
Objective 227
Introduction 227
Web indicators as process indicators 228
Issues of size and reliability 228
Benchmarking indicators 230
Link metrics 230
Relational indicators 232
Other metrics 232
Summary 233
Further reading 233
References 234
VI Summary 237
25 237
Summary 237
Objectives 237
Introduction 237
information science contributions to link analysis 238
Other link analysis approaches 239
Future directions 240
26 241
Glossary 241
References 243
Appendix 245
xii Link Analysis: An Information Science Approach
A SocSciBot tutorial 245
Tutorial 245
Step 1: Installing SocSciBot, SocSciBot Tools and Cyclist 245
Step 2: Installing Pajek 247
Step 3: Crawling a first site with SocSciBot 247
Step 4: Crawling two more sites with SocSciBot 252
Step 5: Viewing basic reports about the small test project with SocSciBot Tools 253
Step 6: Viewing a network diagram with Pajek 257
Step 7: Viewing site diagrams with Pajek 261
Step 8: Using Cyclist 263
Summary 264
Index 265
|
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| title_full | Link analysis an information science approach Mike Thelwall |
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