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digital methods:
foundations and seemingly
        intractable issues.
        prof. dr. Richard Rogers, University of Amsterdam
today.
Situating Digital Methods
Exploring Popular Claims about New
Media with Digital Methods
Web 1.0 vs. Web 2.0 Analysis
Multiple Times Online
The Web as a Problem for Content Analysis
situating
           digital methods I.
1992-1999 Cyberstudies
2000-2007 Virtual Methods
2007-          Digital Methods
situating
         digital methods II.
The approaches within the contemporary
computational turn:
Virtual methods - Digitized methods
Cultural analytics - Digitized content
studies
Digital methods - Natively digital method
for social and cultural research
exploring popular
claims with digital
         methods.
investigating facebook
              activism.
Lonneke van der Velden, PhD candidate, University of Amsterdam
what is facebook activism?

Slacktivism:       “The internet has made “activism” as easy and non-
committal as clicking a mouse button” (Nationalpost.com)

Anti-Facebook:        “Facebook, stop invading my privacy”, Web 2.0
suicide machine, privacy enhancing scripts (New media studies)

Social networking:           “Facebook and other technologies are just
tools to reach out to them [the real social networks, lvdv].” (Advocates for
Science & Technology for the People)
survey digiactive.org.

“Facebook isn’t designed for activism”
“The services may be free, but they have not
been designed to suit your needs as an activist
organizer. This means you will find that the
site's functionality does not always match what
you need. You will have to stretch what is there
in order to be effective.” Dan Schulz, Digiactive.org (2008)
research question.

What kind of activism does Facebook enable?


Which issues do well on Facebook?

What kind of language or practices do they exhibit?

What kind of action is advocated?
locate activism.

Stance language
Facebook-specific ways of phrasing? Instead of issue terms.


Investigate ‘stance’ keywords in page and group titles:
Google Scraper: intitle:support site:facebook.com/group



“anti ” OR “anti-” | against | stop | protest | opposition |
oppose | resistance | resist | halt | refuse | “object to” |
objection | “pro ” OR “pro-” | support | help
DMI Summer 2010 - Final Presentations
zoom in.
Research material:
Google scraper results for the top 100 groups
for “anti”, “pro”, “stop”, and “support” in the
title.
Query the top 35 for member count with “of *
members”, to see which groups are the
biggest.
Note: remove artifacts!
copy paste decoding.
 Question                            Data
To what or to whom is the group     Title/ info keywords
directed?                           following anti, pro, etc
Actor position


What kind of category does the      The group’s category in response to
group submit itself to?             Facebook’s settings
Facebook behaviour


What kind of category can we        Intuitively composed, based on
assign to the group?                keywords (what is the group
Infra-language                      ‘about’)


What kind of engagement or action   The group’s explanation of how to
format does the group suggest?      ‘stop’, ‘support’
Issue language
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
action formats.
What do groups want (users) to do? ‘How’ to
stop/support?
  join, sign, pray, raise awareness, extend
network, etc.


Collated into overlapping action formats
Emerging issue language from the actors’ own
words.
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
calls for action.

Overall, tending towards lightweight engagement and network spread
features of Facebook (learn, join, awareness)
Anti: more action oriented, position of protest
Pro: awareness, spreading
Stop: joining & petitions – specific protests, short term, explicit need
for names on paper
Support: solidarity, letter writing
stretching facebook?
First step towards a different analysis: don’t apply a predefined
notion of activism to your objects or compare object with predefined
“users’ needs”.
Instead: let’s stay close to the objects’ definitions and it’s own
language: what do they call for?
Further research: Bigger samples, interlinking other issue arena’s
within Facebook, associations with sites external to facebook (ie.
“pro-life” –site:facebook.com)
Discussion: Streching Facebook?
DMI Summer 2010 - Final Presentations
investigating facebook activism.


Thank you.

Research: Clare Lee, Esther Weltevrede, Lonneke van der Velden

E-mail: L.C.vanderVelden@uva.nl

Wiki:   wiki.digitalmethods.net/Dmi/TrainingProgramProjectFacebook
the myth of data-driven
           citizen journalism.
Catalina Iorga, RMA student in Media Studies, University of Amsterdam
open data and its benefits.
Transparency

  •   “Transparency is at the heart of this Government.” (data.gov.uk,
         2010)

Democratisation and Citizen Empowerment

  •   “empowering people” (data.gov, 2010)

  •   “these applications arm citizens with the information they need
         to make decisions every day” (data.gov, 2010)

Innovation

  •   Open source software (Jonathan Gray, Open Knowledge, 2010)
data-driven journalism.
Large datasets available online

 •   The Afghan War Diary 2004 - 2010 (WikiLeaks, 2010)

Information visualisation tools

 •   Guardian Data Explorer (Tony Hirst)

A narrative powered by Web 2.0

 •   Using the Web “to tell a story, not just as a delivery
       medium” (Alan Maclean, The New York Times, 2010)
data-driven journalism.



data + tools = info viz <=> new story
research question.


Do non - mainstream digital media (i.e. citizen
 blogs) directly reference Afghan War Diary
 individual document pages?
afghan war diary
“ an extraordinary secret compendium
  of over 91,000 reports covering the
  war in Afghanistan from 2004 to
  2010.”

“ the most significant archive about the
  reality of war to have ever been
  released during the course of a war.”

                         (WikiLeaks, 2010)
       Image source: http://wardiary.wikileaks.org
afghan war diary - der spiegel.




“Deadly Toll”

(Der Spiegel, 2010: http://www.spiegel.de/international/world/bild-708314-114716.html)
afghan war diary - the guardian.




“Afghanistan war logs: IED attacks on civilians, coalition and Afghan troops”

(The Guardian, 2010: http://www.guardian.co.uk/world/datablog/interactive/2010/jul/26/ied-
afghanistan-war-logs)
methodology.
   1. Observe the common root of all Afghan War Diary 2004 - 2010 document
       URLs (‘http://wardiary.wikileaks.org/afg/event').

2. Query Google with the Google Scraper to get the first 1000 results which contain
    this common root as a textual component.

3. Submit the top 100 results to the Link Ripper to extract all outlinks to specific
    Afghan War Diary 2004 - 2010 document pages.

4. Insert the Link Ripper output in the Harvester to remove textual descriptions and
     alphabetize the obtained URL list.

5. Manually clean the output by searching for the 'http://wardiary.wikileaks.org/afg/
    event' and produce a list of Afghan War Diary 2004 - 2010 document URLs.

6 Select all documents that receive at least two links and compile a final list of the
    'most mentioned' warlogs.
methodology - disclaimer.

1. Searching for inlinks with Yahoo! Site Explorer or Google
   yielded the same or no results.

2. Finding inlinks with different anchor tags is very difficult.
findings.
  Content syndication based on local / national interest

  •   Ex.: UK political commentator James Barlow: listing a collection
          of links to warlogs on the British military

Overlap between non-mainstream media and ‘alternative’ accounts

  •   “Idaho Soldier Captured in Afghanistan” (http://
         wardiary.wikileaks.org/afg/event/2009/12/
         AFG20091208n2517.html) - 8 mentions, none alternative

  •   “Four Canadians Killed in Friendly Fire” (http://
         wardiary.wikileaks.org/afg/event/2006/09/
         AFG20060903n347.htm) - 4 mentions, alternative in
         comment spaces
findings.
   “Connect the dots” reasoning in warlog commentary




                                     Text




(Peak of Elephants, Jul 26 2010: http://peakofelephants.posterous.com/post/
    861912878)
conclusion.
Data-driven Citizen Journalism - A Myth

Possible Reasons

 •   massive amount of data

 •   highly technical military terms

 •   pre-determined perspectives by media giants
the myth of data-driven
           citizen journalism.

Thank you.

Research: Camilo Cristancho, Matteo Cernison, Catalina Iorga

E-mail: catalina.iorga@gmail.com

Wiki: wiki.digitalmethods.net/Dmi/DataDrivenUserJournalism
web 1.0 vs web 2.0
analysis and multiple
        times online.
    prof. dr. Richard Rogers,University of Amsterdam
web currencies.
Anne Helmond, PhD candidate, University of Amsterdam
economy of links.

“Links have become the currency of the
Web. With this economic value they also
have power, affecting accessibility and
knowledge on the Web.” Jill Walker (2002)
claim.


“ReTweets Are The New Currency Of
The Web” Michael Arrington, Techcrunch (2009)
claim.


“Google’s Nightmare: Facebook “Like”
Replaces Links” Pete Cashmore (Mashable), CNN (2010)
social currencies.
research questions.

Do social media activities such as the
(re)Tweet or the Like create a web
currency outside of the link?
What type of content is hard to Like and
easy to Like?
method.
1.Query “BP Oil Spill” in Google Web,
  Google Blogs and Google News.
2.Take top 100 results for each sphere
3.Collect number of Diggs, Delicious,
  Tweets and Likes per URL.
4.Manually check for button presence
5.Categorize URLs
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
findings.

Hard to Like:
 Educational, governmental,
 organizational, special interest* and
 wiki websites.
 *outlier: http://paulrademacher.com/oilspill/
findings.

Easy to Like:
  User-generated content platforms &
  Websites connected to a Facebook
  space*
  * BP America & Causes: Help Wildlife Impacted by the BP Oil Spill
DMI Summer 2010 - Final Presentations
findings.
Google ranking is not at all correlated
with any social currencies
Google Web: Like correlates w/ Tweet
Google Blogs: Like correlates w/ Digg
Google News: Like correlates w/ Tweet
web currencies.

Thank you.

Research: Carolin Gerlitz & Anne Helmond

E-mail: anne@digitalmethods.net

Wiki: wiki.digitalmethods.net/Dmi/WebCurrencies2
pace online.
Esther Weltevrede, PhD candidate, University of Amsterdam
internet time.
“Internet Time is absolute time for everybody. Now
is now and the same time for all people and
places.”
                        - Negroponte in Lee and Liebenau, 2000



“Internet time is a multiplicity”
                                                 - Leong 2009
relevance and Internet time.
What does time mean in the different spheres? How
is the temporality of content handled by engines
and platforms?
pace online.
What is pace online?

Update cycles of content
Update cycles of engines
update cycles of content:
                    freshness.
How many blog posts, web pages, tweets, wall
postings are being published every moment on a
specific topic?
DMI Summer 2010 - Final Presentations
update cycles of engines:
                    relevance.
How static or fresh are the result pages of search
engines and platforms?
DMI Summer 2010 - Final Presentations
T 18 Aug 10 15:45 ext   -------------------------3 new results---------------------------   18 Aug 10 15:50
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
no data



no data
no data



no data
no data



no data
‘idle time’
pace online.


Research: Erik Borra, Taina Bucher, Carolin Gerlitz, Anne Helmond,

Esther Weltevrede

Wiki: wiki.digitalmethods.net/Dmi/OneDayOnTheInternetIsEnough

E-mail: esther@digitalmethods.net
the web as a problem
 for content analysis.
     Sabine Niederer, PhD candidate, University of Amsterdam
web content.


“It's early in the twenty-first century, and
that means that these words will mostly
be read by nonpersons." Jaron Lanier 2010
web content.
“The Web didn’t come with content”
Richard Rogers 2010

"Fandom, porn and aliens have taken
cyber-theory into a political and cultural
wasteland" Jodi Dean 2004
"The Web is [where] ignorance meets
egoism meets bad taste meets mob
rule" Andrew Keen 2007
web content.
"[T]he majority of the forum and blog
discussions did not in any way match
the normative criteria of the
Habermasian public sphere" (Thomas Poell 2009)
"It becomes clear that the quality of
the [forum] discussion leaves a lot to
be desired." (Tamara Witschge 2007)
research question.

What kind of content analysis can be
done with the Web?
method follows medium.

 How to let the content speak for itself,
 no coding, or labeling the (sub)
 discourses?
controversy on
              twitter.
Thomas Poell, Assistant Professor, University of Amsterdam
controversy on twitter.




  Thomas Poell, Assistant Professor, University of Amsterdam
Headlines Nytimes & Fox
  Muslim Community Center in Lower Manhattan (Park51)

         Islamic Center Exposes Mixed Feelings Locally

                   Archbishop Offers Mediation for Islamic
                   Center


Under Fire, Obama Clarifies Support for Ground Zero Mosque

         Dozens speak out against planned mosque near
         ground zero at NYC hearing on landmark status

                   Offer Rejected to Move Mosque Away From
                   Ground Zero to 'State Property'
“by letting users tag URLs and then
 aggregating those tags, we're going
 to be able to build alternate
 organizational systems” (Shirky 2008, 18)
research question.


How is controversy organized on Twitter?
1. where can we find the
              controversy on twitter?

 1) Queried the news to find the
 different labels for the controversy.

2) Scraped Twitter for labels to
determine specific hash tags.

3) Calculated the tweet activity per
Twitter query
time to reach 50 tweets.
2. how much of the twitter activity
 is organized through hash tags and
                          retweets?

 1) Divided total number of hashtags
 per Twitter query by the total number
 of tweets for that query = average
 hash tag activity.

2) Divided total number of retweets per
Twitter query by total number tweets for
that query = % of retweet organization.
DMI Summer 2010 - Final Presentations
DMI Summer 2010 - Final Presentations
3. do hash tags organize different
      accounts of the controversy?

1. Determined top hash tags for each
query, and visualized the relative usage.


2. Analyse overlap in related hash tags
between queries.
#fb                                      Facebook


 #gop                               Grand Old Party


 #gzm                           Ground Zero Mosque

          Organized Conservative Resistance Alliance
 #ocra

                                    Progressives 2.0
 #p2


#palin                                   Sarah Palin


#park51           location Islamic community Center


 #rsrh                            Red State Red Hot


 #sgp      Smart Girl Politics (Conservative Women)


 #tcot                   Top Conservatives on Twitter


 #tlot                   Top Libertarians on Twitter
Ground Zero Mosque
#gzm
#Mosque
New York Islamic Center
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4. does retweeting produce
       distinctly different accounts?


1. Select the top retweets per query.


2. Compare accounts.
Ground Zero Mosque

   1. RT@Douggpound: How come everyone is up in arms about that
   mosque but no one cares about Coke Ground Zero? (59)

2. RT @ewerickson: A lesson in tolerance from the left:Tolerance =
Ground Zero Mosque. Intolerance = @GlennBeck speaking at the
Lincoln Memorial.#rsrh #fb (19)

3. RT @ewerickson: Holocaust survivor cursed out by Ground Zero
Mosque supporter. Because it's all about tolerance. Really. http://
is.gd/eD43a (18)
#gzm

   1. RT @MitchBenn: Re. "#gzm" (misnomer but used for ease of
   ref.): trouble with Muslim Terrorists isn't that they're Muslims.
   It's that they're terrorists... (14)

2. RT @JordanSekulow: This cartoon on #GZM, Obama, & Israel is
so dead on http://bit.ly/bIURiG (13)

3. RT @TuckerCarlson: RT @DailyCaller: U.S. government funds
mosque renovation and rehabilitation around the world http://
ow.ly/2tWP6 #gzm (9)
New York Islamic Center

  1. RT @cnnbrk: Protesters rally against, for planned Islamic center
  in New York. http://on.cnn.com/9MZJm6 (107)

2. RT @AndersonCooper: Imam behind controversial New York Islamic
center speaks http://bit.ly/aXAOBG (21)

3. RT @AlanColmes: Imam Behind New York Islamic Center Speaks
http://bit.ly/b8vXCp #p2 (11)
conclusions.

Two types of users


Spaces of confrontation
controversy on twitter.

Thank you.

Research: Matteo Cernison, Simeona Petkova & Thomas Poell

E-mail: Poell@uva.nl

Wiki: http://wiki.digitalmethods.net/Dmi/SelfOrganizingContent
related search.
  Erik Borra, Docent, University of Amsterdam
DMI Summer 2010 - Final Presentations
what is related search?
it is not based on query logs

it portrays semantic clusters of Web documents
it has generative rules to suggest different terms
challenge.
Can the related search option be turned into a
research tool?
the good news:
Google's related searches allow to "scan" broad
thematic landscapes quickly


                            the bad news:
Google's related searches tend to go mad:
- Topic drifting (usual)
- Over-generative (unusual)
google examples.
- "Global Warning"
- "Global Warming Is An Idiot"
- "Al Gore Isnt Real"

Too much generativity and not enough selectivity.
strategies to counter act that.
A high threshold of connectivity reveals when
suggestions become inconsistent: No more path to
known terms
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                                                                                        Footprint
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                                                                                                                                                                    A&,*.

                                                                        Define
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                                                                                                                                                                                                                                                   /.00




                                                                                                                                                                                                                                                      Global Warming
                                                                                                                                                                                                                                                         Skeptics


                                                                                                                                                                 Junk
                                                                                                                                                                Science
related search as a re-
                        search tool.
organization of a content space
query-design
starting-points
identification of programs / anti-programs
classification and categorization
related search.

Thank you.

Research: Mathieu Jacomy, Matthieu Renault, Esther Weltevrede & Erik

Borra

E-mail: erik@digitalmethods.net

Wiki: wiki.digitalmethods.net/Dmi/RelatedSearchAsQueryDesign
digital methods
                 initiative
     summer school 2010.
Thank you.

E-mail: info@digitalmethods.net

Wiki: http://summer2010.digitalmethods.net

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DMI Summer 2010 - Final Presentations

  • 1. digital methods: foundations and seemingly intractable issues. prof. dr. Richard Rogers, University of Amsterdam
  • 2. today. Situating Digital Methods Exploring Popular Claims about New Media with Digital Methods Web 1.0 vs. Web 2.0 Analysis Multiple Times Online The Web as a Problem for Content Analysis
  • 3. situating digital methods I. 1992-1999 Cyberstudies 2000-2007 Virtual Methods 2007-          Digital Methods
  • 4. situating digital methods II. The approaches within the contemporary computational turn: Virtual methods - Digitized methods Cultural analytics - Digitized content studies Digital methods - Natively digital method for social and cultural research
  • 5. exploring popular claims with digital methods.
  • 6. investigating facebook activism. Lonneke van der Velden, PhD candidate, University of Amsterdam
  • 7. what is facebook activism? Slacktivism: “The internet has made “activism” as easy and non- committal as clicking a mouse button” (Nationalpost.com) Anti-Facebook: “Facebook, stop invading my privacy”, Web 2.0 suicide machine, privacy enhancing scripts (New media studies) Social networking: “Facebook and other technologies are just tools to reach out to them [the real social networks, lvdv].” (Advocates for Science & Technology for the People)
  • 8. survey digiactive.org. “Facebook isn’t designed for activism” “The services may be free, but they have not been designed to suit your needs as an activist organizer. This means you will find that the site's functionality does not always match what you need. You will have to stretch what is there in order to be effective.” Dan Schulz, Digiactive.org (2008)
  • 9. research question. What kind of activism does Facebook enable? Which issues do well on Facebook? What kind of language or practices do they exhibit? What kind of action is advocated?
  • 10. locate activism. Stance language Facebook-specific ways of phrasing? Instead of issue terms. Investigate ‘stance’ keywords in page and group titles: Google Scraper: intitle:support site:facebook.com/group “anti ” OR “anti-” | against | stop | protest | opposition | oppose | resistance | resist | halt | refuse | “object to” | objection | “pro ” OR “pro-” | support | help
  • 12. zoom in. Research material: Google scraper results for the top 100 groups for “anti”, “pro”, “stop”, and “support” in the title. Query the top 35 for member count with “of * members”, to see which groups are the biggest. Note: remove artifacts!
  • 13. copy paste decoding. Question Data To what or to whom is the group Title/ info keywords directed? following anti, pro, etc Actor position What kind of category does the The group’s category in response to group submit itself to? Facebook’s settings Facebook behaviour What kind of category can we Intuitively composed, based on assign to the group? keywords (what is the group Infra-language ‘about’) What kind of engagement or action The group’s explanation of how to format does the group suggest? ‘stop’, ‘support’ Issue language
  • 19. action formats. What do groups want (users) to do? ‘How’ to stop/support? join, sign, pray, raise awareness, extend network, etc. Collated into overlapping action formats Emerging issue language from the actors’ own words.
  • 22. calls for action. Overall, tending towards lightweight engagement and network spread features of Facebook (learn, join, awareness) Anti: more action oriented, position of protest Pro: awareness, spreading Stop: joining & petitions – specific protests, short term, explicit need for names on paper Support: solidarity, letter writing
  • 23. stretching facebook? First step towards a different analysis: don’t apply a predefined notion of activism to your objects or compare object with predefined “users’ needs”. Instead: let’s stay close to the objects’ definitions and it’s own language: what do they call for? Further research: Bigger samples, interlinking other issue arena’s within Facebook, associations with sites external to facebook (ie. “pro-life” –site:facebook.com) Discussion: Streching Facebook?
  • 25. investigating facebook activism. Thank you. Research: Clare Lee, Esther Weltevrede, Lonneke van der Velden E-mail: L.C.vanderVelden@uva.nl Wiki: wiki.digitalmethods.net/Dmi/TrainingProgramProjectFacebook
  • 26. the myth of data-driven citizen journalism. Catalina Iorga, RMA student in Media Studies, University of Amsterdam
  • 27. open data and its benefits. Transparency • “Transparency is at the heart of this Government.” (data.gov.uk, 2010) Democratisation and Citizen Empowerment • “empowering people” (data.gov, 2010) • “these applications arm citizens with the information they need to make decisions every day” (data.gov, 2010) Innovation • Open source software (Jonathan Gray, Open Knowledge, 2010)
  • 28. data-driven journalism. Large datasets available online • The Afghan War Diary 2004 - 2010 (WikiLeaks, 2010) Information visualisation tools • Guardian Data Explorer (Tony Hirst) A narrative powered by Web 2.0 • Using the Web “to tell a story, not just as a delivery medium” (Alan Maclean, The New York Times, 2010)
  • 29. data-driven journalism. data + tools = info viz <=> new story
  • 30. research question. Do non - mainstream digital media (i.e. citizen blogs) directly reference Afghan War Diary individual document pages?
  • 31. afghan war diary “ an extraordinary secret compendium of over 91,000 reports covering the war in Afghanistan from 2004 to 2010.” “ the most significant archive about the reality of war to have ever been released during the course of a war.” (WikiLeaks, 2010) Image source: http://wardiary.wikileaks.org
  • 32. afghan war diary - der spiegel. “Deadly Toll” (Der Spiegel, 2010: http://www.spiegel.de/international/world/bild-708314-114716.html)
  • 33. afghan war diary - the guardian. “Afghanistan war logs: IED attacks on civilians, coalition and Afghan troops” (The Guardian, 2010: http://www.guardian.co.uk/world/datablog/interactive/2010/jul/26/ied- afghanistan-war-logs)
  • 34. methodology. 1. Observe the common root of all Afghan War Diary 2004 - 2010 document URLs (‘http://wardiary.wikileaks.org/afg/event'). 2. Query Google with the Google Scraper to get the first 1000 results which contain this common root as a textual component. 3. Submit the top 100 results to the Link Ripper to extract all outlinks to specific Afghan War Diary 2004 - 2010 document pages. 4. Insert the Link Ripper output in the Harvester to remove textual descriptions and alphabetize the obtained URL list. 5. Manually clean the output by searching for the 'http://wardiary.wikileaks.org/afg/ event' and produce a list of Afghan War Diary 2004 - 2010 document URLs. 6 Select all documents that receive at least two links and compile a final list of the 'most mentioned' warlogs.
  • 35. methodology - disclaimer. 1. Searching for inlinks with Yahoo! Site Explorer or Google yielded the same or no results. 2. Finding inlinks with different anchor tags is very difficult.
  • 36. findings. Content syndication based on local / national interest • Ex.: UK political commentator James Barlow: listing a collection of links to warlogs on the British military Overlap between non-mainstream media and ‘alternative’ accounts • “Idaho Soldier Captured in Afghanistan” (http:// wardiary.wikileaks.org/afg/event/2009/12/ AFG20091208n2517.html) - 8 mentions, none alternative • “Four Canadians Killed in Friendly Fire” (http:// wardiary.wikileaks.org/afg/event/2006/09/ AFG20060903n347.htm) - 4 mentions, alternative in comment spaces
  • 37. findings. “Connect the dots” reasoning in warlog commentary Text (Peak of Elephants, Jul 26 2010: http://peakofelephants.posterous.com/post/ 861912878)
  • 38. conclusion. Data-driven Citizen Journalism - A Myth Possible Reasons • massive amount of data • highly technical military terms • pre-determined perspectives by media giants
  • 39. the myth of data-driven citizen journalism. Thank you. Research: Camilo Cristancho, Matteo Cernison, Catalina Iorga E-mail: catalina.iorga@gmail.com Wiki: wiki.digitalmethods.net/Dmi/DataDrivenUserJournalism
  • 40. web 1.0 vs web 2.0 analysis and multiple times online. prof. dr. Richard Rogers,University of Amsterdam
  • 41. web currencies. Anne Helmond, PhD candidate, University of Amsterdam
  • 42. economy of links. “Links have become the currency of the Web. With this economic value they also have power, affecting accessibility and knowledge on the Web.” Jill Walker (2002)
  • 43. claim. “ReTweets Are The New Currency Of The Web” Michael Arrington, Techcrunch (2009)
  • 44. claim. “Google’s Nightmare: Facebook “Like” Replaces Links” Pete Cashmore (Mashable), CNN (2010)
  • 46. research questions. Do social media activities such as the (re)Tweet or the Like create a web currency outside of the link? What type of content is hard to Like and easy to Like?
  • 47. method. 1.Query “BP Oil Spill” in Google Web, Google Blogs and Google News. 2.Take top 100 results for each sphere 3.Collect number of Diggs, Delicious, Tweets and Likes per URL. 4.Manually check for button presence 5.Categorize URLs
  • 51. findings. Hard to Like: Educational, governmental, organizational, special interest* and wiki websites. *outlier: http://paulrademacher.com/oilspill/
  • 52. findings. Easy to Like: User-generated content platforms & Websites connected to a Facebook space* * BP America & Causes: Help Wildlife Impacted by the BP Oil Spill
  • 54. findings. Google ranking is not at all correlated with any social currencies Google Web: Like correlates w/ Tweet Google Blogs: Like correlates w/ Digg Google News: Like correlates w/ Tweet
  • 55. web currencies. Thank you. Research: Carolin Gerlitz & Anne Helmond E-mail: anne@digitalmethods.net Wiki: wiki.digitalmethods.net/Dmi/WebCurrencies2
  • 56. pace online. Esther Weltevrede, PhD candidate, University of Amsterdam
  • 57. internet time. “Internet Time is absolute time for everybody. Now is now and the same time for all people and places.” - Negroponte in Lee and Liebenau, 2000 “Internet time is a multiplicity” - Leong 2009
  • 58. relevance and Internet time. What does time mean in the different spheres? How is the temporality of content handled by engines and platforms?
  • 59. pace online. What is pace online? Update cycles of content Update cycles of engines
  • 60. update cycles of content: freshness. How many blog posts, web pages, tweets, wall postings are being published every moment on a specific topic?
  • 62. update cycles of engines: relevance. How static or fresh are the result pages of search engines and platforms?
  • 64. T 18 Aug 10 15:45 ext -------------------------3 new results--------------------------- 18 Aug 10 15:50
  • 71. pace online. Research: Erik Borra, Taina Bucher, Carolin Gerlitz, Anne Helmond, Esther Weltevrede Wiki: wiki.digitalmethods.net/Dmi/OneDayOnTheInternetIsEnough E-mail: esther@digitalmethods.net
  • 72. the web as a problem for content analysis. Sabine Niederer, PhD candidate, University of Amsterdam
  • 73. web content. “It's early in the twenty-first century, and that means that these words will mostly be read by nonpersons." Jaron Lanier 2010
  • 74. web content. “The Web didn’t come with content” Richard Rogers 2010 "Fandom, porn and aliens have taken cyber-theory into a political and cultural wasteland" Jodi Dean 2004 "The Web is [where] ignorance meets egoism meets bad taste meets mob rule" Andrew Keen 2007
  • 75. web content. "[T]he majority of the forum and blog discussions did not in any way match the normative criteria of the Habermasian public sphere" (Thomas Poell 2009) "It becomes clear that the quality of the [forum] discussion leaves a lot to be desired." (Tamara Witschge 2007)
  • 76. research question. What kind of content analysis can be done with the Web?
  • 77. method follows medium. How to let the content speak for itself, no coding, or labeling the (sub) discourses?
  • 78. controversy on twitter. Thomas Poell, Assistant Professor, University of Amsterdam
  • 79. controversy on twitter. Thomas Poell, Assistant Professor, University of Amsterdam
  • 80. Headlines Nytimes & Fox Muslim Community Center in Lower Manhattan (Park51) Islamic Center Exposes Mixed Feelings Locally Archbishop Offers Mediation for Islamic Center Under Fire, Obama Clarifies Support for Ground Zero Mosque Dozens speak out against planned mosque near ground zero at NYC hearing on landmark status Offer Rejected to Move Mosque Away From Ground Zero to 'State Property'
  • 81. “by letting users tag URLs and then aggregating those tags, we're going to be able to build alternate organizational systems” (Shirky 2008, 18)
  • 82. research question. How is controversy organized on Twitter?
  • 83. 1. where can we find the controversy on twitter? 1) Queried the news to find the different labels for the controversy. 2) Scraped Twitter for labels to determine specific hash tags. 3) Calculated the tweet activity per Twitter query
  • 84. time to reach 50 tweets.
  • 85. 2. how much of the twitter activity is organized through hash tags and retweets? 1) Divided total number of hashtags per Twitter query by the total number of tweets for that query = average hash tag activity. 2) Divided total number of retweets per Twitter query by total number tweets for that query = % of retweet organization.
  • 88. 3. do hash tags organize different accounts of the controversy? 1. Determined top hash tags for each query, and visualized the relative usage. 2. Analyse overlap in related hash tags between queries.
  • 89. #fb Facebook #gop Grand Old Party #gzm Ground Zero Mosque Organized Conservative Resistance Alliance #ocra Progressives 2.0 #p2 #palin Sarah Palin #park51 location Islamic community Center #rsrh Red State Red Hot #sgp Smart Girl Politics (Conservative Women) #tcot   Top Conservatives on Twitter #tlot Top Libertarians on Twitter
  • 91. #gzm
  •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
  • 95. 4. does retweeting produce distinctly different accounts? 1. Select the top retweets per query. 2. Compare accounts.
  • 96. Ground Zero Mosque 1. RT@Douggpound: How come everyone is up in arms about that mosque but no one cares about Coke Ground Zero? (59) 2. RT @ewerickson: A lesson in tolerance from the left:Tolerance = Ground Zero Mosque. Intolerance = @GlennBeck speaking at the Lincoln Memorial.#rsrh #fb (19) 3. RT @ewerickson: Holocaust survivor cursed out by Ground Zero Mosque supporter. Because it's all about tolerance. Really. http:// is.gd/eD43a (18)
  • 97. #gzm 1. RT @MitchBenn: Re. "#gzm" (misnomer but used for ease of ref.): trouble with Muslim Terrorists isn't that they're Muslims. It's that they're terrorists... (14) 2. RT @JordanSekulow: This cartoon on #GZM, Obama, & Israel is so dead on http://bit.ly/bIURiG (13) 3. RT @TuckerCarlson: RT @DailyCaller: U.S. government funds mosque renovation and rehabilitation around the world http:// ow.ly/2tWP6 #gzm (9)
  • 98. New York Islamic Center 1. RT @cnnbrk: Protesters rally against, for planned Islamic center in New York. http://on.cnn.com/9MZJm6 (107) 2. RT @AndersonCooper: Imam behind controversial New York Islamic center speaks http://bit.ly/aXAOBG (21) 3. RT @AlanColmes: Imam Behind New York Islamic Center Speaks http://bit.ly/b8vXCp #p2 (11)
  • 99. conclusions. Two types of users Spaces of confrontation
  • 100. controversy on twitter. Thank you. Research: Matteo Cernison, Simeona Petkova & Thomas Poell E-mail: Poell@uva.nl Wiki: http://wiki.digitalmethods.net/Dmi/SelfOrganizingContent
  • 101. related search. Erik Borra, Docent, University of Amsterdam
  • 103. what is related search? it is not based on query logs it portrays semantic clusters of Web documents it has generative rules to suggest different terms
  • 104. challenge. Can the related search option be turned into a research tool?
  • 105. the good news: Google's related searches allow to "scan" broad thematic landscapes quickly the bad news: Google's related searches tend to go mad: - Topic drifting (usual) - Over-generative (unusual)
  • 106. google examples. - "Global Warning" - "Global Warming Is An Idiot" - "Al Gore Isnt Real" Too much generativity and not enough selectivity.
  • 107. strategies to counter act that. A high threshold of connectivity reveals when suggestions become inconsistent: No more path to known terms
  • 108. !"#$%"&'7"$)*+8888888888888888888888888888888888 4565 !"#$%"&'("$)*+"(',-)'.#-/$#'0$)1234 A#/'(/'*&/&2,"%"*-%':*1##02(*.(2&'()*"(&.$:B !""#$%&'()*+(,-#.)"*&$$#.)%/0*'#*1##02( 7%0%'&2*8(':#)"*;<==(.*;$:##2 !)>&/$()*?.#0.&=*?.#@($'" 56 * !"("$)*+88&':%(<*C&$#=,D*E.%+*F#..&D*8&'':%(<*G(/&<2'D* -7.$&'(/&+0(!" Global Warming #=..(!"(3''$6 E"':(.*H(2'(>.()(* 9"%+-&8I<(.,*J12#K&2*H&.=%/0L*%/*1##02(*&/)*.('.%(>(* Literacy ':(*.(2&'()*"(&.$:("*-:%$:*$#M#$$<.*=#"'B**N%"<&2%O(* #=..(!"(?$0.= -%':*1(P:%B#.0D*.(P2&$(*&22*=(/'%#/"*#Q*12#K&2*H&.=%/0* K,*1H*&/)*&//#'&'(B Air :$%$R0&':(.()R-3R4S*!<0<"' 3*4565*789 !"(<$&$(;$'$ Pollution !"(3''$6 Car !"(@.'.$=%7(?$0.= !"(?$0.= Pollution !"(/0..%7 !=$07'(:4(!" Pollution !"()44.%&' !"(-$,'.' !"(3''$6' Causes "7$&(-$,'.'(!" 344.%&'(:4(!" Causes & Effects Types of /&+0(!" !"(344.%&' Pollution & Effects #$%&'(:4(!" !"(<$&$ !"(-7$=&' -$,'.'(:4(!" !"(@.'.$=%7 -4% -$=(327$,'& !"(!=$07' Global Warming !"(#$'&(#$%&' !"(-7$=& !"(/&$&' Anti-Global Warming Greenhouse Science 89(#$%&'(!" ?=+(!"(#$%&' !"(#$%&' #$%&'()*+,&(!" !"(@.0+=& "$&.= 3$=&7 !"(!=$07 !"(5$0 !"(5$0' ?=+(!" 30$ !"(#+=.%$'& 3$=&7(<$6(#$%&' !"(?=++4 56&7'()*+,&(!" !"(56&7' 3%+(#$%&' 3$=&7(<$6 !" Al Gore ?=++4(:4(!" !"(1+$2 !"(#$=%. Green Facts Climate !"(<.*$&. A'(5$0 Global Warming !"(1+$2(>*% & Tips Change Hoax 5$0' !"(56&7 Footprint Climate Change Energy Media Controversy Solution Conservation ;$'$ ;+$$ A&,*. Define Global Warming Global Warming <+&(3$=&7 Swindle Media /.00 Global Warming Skeptics Junk Science
  • 109. related search as a re- search tool. organization of a content space query-design starting-points identification of programs / anti-programs classification and categorization
  • 110. related search. Thank you. Research: Mathieu Jacomy, Matthieu Renault, Esther Weltevrede & Erik Borra E-mail: erik@digitalmethods.net Wiki: wiki.digitalmethods.net/Dmi/RelatedSearchAsQueryDesign
  • 111. digital methods initiative summer school 2010. Thank you. E-mail: info@digitalmethods.net Wiki: http://summer2010.digitalmethods.net