The Ethics of LargeScale Web Data Analysis Webmetrics

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The Ethics of Large-Scale Web Data Analysis
(Webmetrics)

• Mike Thelwall, Statistical Cybermetrics Research
  Group, University of Wolverhampton, UK
• Rob Ackland, Australian Demographic and Social
  Research Institute, Australian National University

Virtual Knowledge Studio (VKS)
Information Studies
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Contents

• What is webmetrics?
• Context Online access to personal information
• Researchers use of personal information
• Confidentiality and anonymity
• Resource issues
• What ethical considerations apply to collecting
  and analysing web data on a large scale from
  unaware web publishers ?

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1. What is webmetrics?

• Large-scale analysis if web-based data
• Collecting and quantitatively analysing online
  information
• Objective is not to find information about
  individuals but identify trends
• Data gathered with VOSON, SocSciBot, Issue
  Crawler, LexiURL,

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Example

• VOSON Hyperlink
• network of
• political parties
• from 6 countries
• (Ackland and
• Gibson, 2006).
• Node size prop.
• to outdegree.
• 76 nodes.

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Austria
Geopolitical connected
Switzerland
Example Links between EU universities
Belgium
Germany
France
Spain
NL
UK
Norway
Italy
Poland
Finland
Sweden
AltaVista link searches
Normalised linking, smallest countries removed
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Link associations between social network sites
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Example Blog searching
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2. Context Online access to personal information

• Blogs, social network sites, personal web sites
  contain information that is
• Private and protected (invisible to researchers)
• Intentionally public
• Publicly private1 (intended for friends but
  allowed to be public)
• Unintentionally public (public but believed by
  owner to be private)

1. Lang (2007)
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Accessing public information

• Commercial search engines
• Web crawlers
• Internet Archive (includes deleted info)

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Who is using Dataveillance?

• Dataveillance1 Downloading or otherwise
  gathering data on internet users in order to
  influence their behaviour
• Google can use email, searching, blogging,
  social network activities to target advertising
  ( may report to US government)
• Amazon can use past activities to target
  adverts or improve web site

1. Zimmer (2008)
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3. Researchers use of personal information

• Key issue for large scale research, data
  from/about the unaware is used without their
  approval, and possibly for purposes that they
  might disagree with
• Which ethical safeguards should be taken for this
  kind of research?

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Issue 1 People vs. Documents

• Traditionally, documents can be researched
  without approval, but people cant
• Even harsh criticism is fair practice (e.g., book
  review/analysis)
• Since web pages are documents, researching them
  without permission is normally OK

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Issue 2 Invasion of privacy? Natural vs.
normative

• A situation is naturally private1 if a reasonable
  person would expect privacy
• A situation is normatively private1 if a
  reasonable person would expect others to protect
  their privacy
• Non-secure web pages/data are typically naturally
  private
• Accessing is not normally invading privacy, even
  if undesired by page owners and with negative
  consequences

1. Moor (2004)
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4. Confidentiality and anonymity

• When should anonymity be granted to research
  subjects (page owners)?
• When a possibly undesired label attached (e.g.,
  hate group, terrorist)
• When undesired groups might benefit? (e.g.,
  league table of hate groups)
• When publicly private individuals singled out
  (e.g., detailed analysis of average blogger)
• Should data be anonymised as for Census data
  used for research?

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5. Resource issues

• Accessing a web page uses the owners server
  time/bandwidth
• Crawling a web site can use a lot of the owners
  server time/bandwidth
• May incur charges or loss of service quality

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Robots.txt protocol

• This file lists pages/folders in a web site may
  not be crawled
• It does not restrict crawling speed
• It should be obeyed in research
• Most individual users are probably unaware of
  this and so dont use its protection

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Crawling speed

• Web crawlers should not run too fast that they
  cause service issues
• Full speed is probably OK on a UK university web
  site but not on a Burkina Faso library web site
• Use judgement to decide how quickly to crawl
  length of pauses in crawling

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How many pages to crawl?

• Crawling too many pages puts unnecessary strain
  on the server crawled
• Use judgement to decide the minimum number of
  pages/crawl depth that is enough
• Use search engine queries as a substitute, if
  possible

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Automatic search engine searches

• Research can piggyback off the crawling of
  commercial search engines
• No resource implications for site owners
• Uses search engine Applications Programming
  Interfaces
• Search engines specify the maximum number of
  searches per day
• Results limited to the imperfect web
  crawling/coverage of search engine crawlers

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Summary

• Researchers need to be aware of potential issues
  when doing large scale data analysis research
• Judgement is called for in all issues
• Research does not normally need participant
  permission
• Be sensitive to impact of findings and any need
  for anonymity

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References

• Lange, P. G. (2007). Publicly private and
  privately public Social networking on YouTube.
  Journal of Computer-Mediated Communication,
  13(1), Retrieved May 8, 2008 from
  http//jcmc.indiana.edu/vol2013/issue2001/lange.ht
  ml
• Zimmer, M. (2008). The gaze of the perfect search
  engine Google as an infrastructure of
  dataveillance. In A. Spink M. Zimmer (Eds.),
  Web search Multidisciplinary perspectives (pp.
  77-99). Berlin Springer.
• Moor, J. H. (2004). Towards a theory of privacy
  for the information age. In R. A. Spinello H.
  T. Tavani (Eds.), Readings in CyberEthics (2nd
  ed., pp. 407-417). Sudbury, MA Jones and
  Bartlett.