DMI Summer 2010 - Final Presentations

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DMI Summer 2010 - Final Presentations

  1. 1. digital methods: foundations and seemingly intractable issues. prof. dr. Richard Rogers, University of Amsterdam
  2. 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. 3. situating digital methods I. 1992-1999 Cyberstudies 2000-2007 Virtual Methods 2007-          Digital Methods
  4. 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. 5. exploring popular claims with digital methods.
  6. 6. investigating facebook activism. Lonneke van der Velden, PhD candidate, University of Amsterdam
  7. 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. 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. 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. 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
  11. 11. 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!
  12. 12. 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
  13. 13. 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.
  14. 14. 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
  15. 15. 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?
  16. 16. 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
  17. 17. the myth of data-driven citizen journalism. Catalina Iorga, RMA student in Media Studies, University of Amsterdam
  18. 18. 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)
  19. 19. 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)
  20. 20. data-driven journalism. data + tools = info viz <=> new story
  21. 21. research question. Do non - mainstream digital media (i.e. citizen blogs) directly reference Afghan War Diary individual document pages?
  22. 22. 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
  23. 23. afghan war diary - der spiegel. “Deadly Toll” (Der Spiegel, 2010: http://www.spiegel.de/international/world/bild-708314-114716.html)
  24. 24. 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)
  25. 25. 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.
  26. 26. 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.
  27. 27. 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
  28. 28. findings. “Connect the dots” reasoning in warlog commentary Text (Peak of Elephants, Jul 26 2010: http://peakofelephants.posterous.com/post/ 861912878)
  29. 29. conclusion. Data-driven Citizen Journalism - A Myth Possible Reasons • massive amount of data • highly technical military terms • pre-determined perspectives by media giants
  30. 30. 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
  31. 31. web 1.0 vs web 2.0 analysis and multiple times online. prof. dr. Richard Rogers,University of Amsterdam
  32. 32. web currencies. Anne Helmond, PhD candidate, University of Amsterdam
  33. 33. 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)
  34. 34. claim. “ReTweets Are The New Currency Of The Web” Michael Arrington, Techcrunch (2009)
  35. 35. claim. “Google’s Nightmare: Facebook “Like” Replaces Links” Pete Cashmore (Mashable), CNN (2010)
  36. 36. social currencies.
  37. 37. 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?
  38. 38. 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
  39. 39. findings. Hard to Like: Educational, governmental, organizational, special interest* and wiki websites. *outlier: http://paulrademacher.com/oilspill/
  40. 40. 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
  41. 41. 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
  42. 42. web currencies. Thank you. Research: Carolin Gerlitz & Anne Helmond E-mail: anne@digitalmethods.net Wiki: wiki.digitalmethods.net/Dmi/WebCurrencies2
  43. 43. pace online. Esther Weltevrede, PhD candidate, University of Amsterdam
  44. 44. 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
  45. 45. relevance and Internet time. What does time mean in the different spheres? How is the temporality of content handled by engines and platforms?
  46. 46. pace online. What is pace online? Update cycles of content Update cycles of engines
  47. 47. update cycles of content: freshness. How many blog posts, web pages, tweets, wall postings are being published every moment on a specific topic?
  48. 48. update cycles of engines: relevance. How static or fresh are the result pages of search engines and platforms?
  49. 49. T 18 Aug 10 15:45 ext -------------------------3 new results--------------------------- 18 Aug 10 15:50
  50. 50. no data no data
  51. 51. no data no data
  52. 52. no data no data
  53. 53. ‘idle time’
  54. 54. pace online. Research: Erik Borra, Taina Bucher, Carolin Gerlitz, Anne Helmond, Esther Weltevrede Wiki: wiki.digitalmethods.net/Dmi/OneDayOnTheInternetIsEnough E-mail: esther@digitalmethods.net
  55. 55. the web as a problem for content analysis. Sabine Niederer, PhD candidate, University of Amsterdam
  56. 56. 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
  57. 57. 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
  58. 58. 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)
  59. 59. research question. What kind of content analysis can be done with the Web?
  60. 60. method follows medium. How to let the content speak for itself, no coding, or labeling the (sub) discourses?
  61. 61. controversy on twitter. Thomas Poell, Assistant Professor, University of Amsterdam
  62. 62. controversy on twitter. Thomas Poell, Assistant Professor, University of Amsterdam
  63. 63. 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'
  64. 64. “by letting users tag URLs and then aggregating those tags, we're going to be able to build alternate organizational systems” (Shirky 2008, 18)
  65. 65. research question. How is controversy organized on Twitter?
  66. 66. 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
  67. 67. time to reach 50 tweets.
  68. 68. 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.
  69. 69. 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.
  70. 70. #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
  71. 71. Ground Zero Mosque
  72. 72. #gzm
  73. 73. #Mosque
  74. 74. New York Islamic Center
  75. 75. !&0#5+"0&&.* !0#$- !+,3" !#*$'+ !:,3443"9:. !2;>4 !788:%4 !*.'9&)3#0-+ !-$2;4 !:0-3.)'.0*) !788:;4 !$*/.))30- !#.-+$*+,3' !3*0? !'0 !*0#3+" !+"$'",.4$+?9. !63,0:/0"#, !3-:30 !#$-2*.++ !'0"*3$"+ !:94& !2;4$+?9. !/"#4$+?9. !$''*.++3$- !'(8 !0*0&+ !&)04.&9+, !%0#" !,3"#,.-+ !*0#3+4 !'0)3- !)3&.*0) !&32$" !,#* !3404%.3+0)*09% !,3+"$*1 !'.)$+3 !$&040B+ !"/3+".* !"*9", !'*$'D !,$)$#09+" !&32$"*1 !$&040%03) !+".0)",63,0: !.4'3*. !6./ !+,.**$: !0%2,0-3+"0- !+$" !3404 !,0".#*34.C3)).20) !40::$/ !#$-+.*>0"3>.+ !#$43#+ !3404*09% !2*..- !5$*0- !&+ !1$95-$//,0"+0--$13-2 !2; !0")0++,*92+ !&32$"+ !0*#,3".#"9*. !&0&3.+ !:03)1+,$/ !#+'6 !%.0* !"'' !3-".*%03", !#$-+"3"9"3$- !/0* !&9*- *$+12.'3#..$%245'3)%4)" !#,0*)3.&*$$5.* !5$#, !",.:03)1+,$/ -/0. !3+)043# !*.)323$- !)0;3$ !".**$* !-./1$*5#3"1 !)3&.*0)+ !/353).05+ !&0*&0*3# !)..: !/"# !'.0#. !-1" -/"#$%&0)"#.#+,$) !*09% !*040:0- !#$)&.*" !+09:3 !2$$: !/$*):"*0:.#.-".* !49*:$#, !#,*3+"30- !'( !-.>.*%$*2." !$&040 !3+)04 !A !-$4$+?9. !788"*9", !/"% !*.3: !5.--1 !:.4+ !".0'0*"1 !7 !04.*3#0 !'*$2 !#-- !2*$9-:;.*$ !&)$$4&.*2 !6$9*-$)3+" !".**$*3+4 !%& !&0*0#5$&040 !>3:.$ !4+-&# !#$*:$&0 !49+)34 !*9'.*"49*:$#, !)2&" !#0*"$$- !".0#,3-2 !2$' !3*0- !-0;3 !#9$4$ -.#+,$) !'(& !+,0*30 !-1# !'*$".+" !3-"$).*0-#. !:98 !?9$". !%.3+0) !3-#.'"3$- !*.:.1. !-./+ !.->3*$-4.-" !%03) !3+*0.) !"&*+ !#$44$-+.-+. !788 !-1 !49+)34+ !2).--&.#5 !")$" !%$=-./+ !6#$" !3*0-.).#"3$- !&.#5 !'0*5@8 6)7'8#"9':+1;.2<'3)%4)" !304",.4$& !4.:30 !3+)04$',$&30 !,,*+ !6./+ !+2' !-./1$*5 !9+0 !#0",$)3# !:-# !63,0: !"$).*0-#. !6)$" !%$= !0&# !%*..:$4 !"3$" !*+ !#,9*#, !"#$" !78( !#.-".* !/$*): !04.*3#0- !$#*0 !"$''*$2 !9#$" !)3&.*"1 !*9+, !2*$9-: !,9%%'$+" !*0))1 !95 !"/3+".*+ !'053+"0- !:.4 !4+4 !)3&.*"0*30- !5..'4. !#&+ !+.$ !40-,0""0- !6./3+, !,0". !8 !#$-+.*>0"3>. !'$)3"3#+ !;.*$ !%*..+'..#, !201 !3- !2$: !-$2*$9-:;.*$4$+?9. !,$4.)0-: !#,3#02$ !?9*0- !9+ !2/$" !*'- !*3:3#9)$9+ !#$*:$&0,$9+. !43)3"0*1 !3) !#$-+-# !'0"*3$" !-&# !0-"3+.43"3+4 !@8'0*5 !3))3-$3+ !0*41 !04'0" !*+*, !-6 !0<0 !69+"+013- !"#$%&'()"#'*#+,$) !6.+9+ !'0"*3$""/.."+ !,3',$' !*$-'09) !4.4.$ !:.4$#*0" !9"'$) !-./ !+"$'&.#5 !0))0, !#0)3%$*-30 !69+"+013-2 !&)04.788>3#"34+ !:0:" !6$-+"./0*" !&&# !):+ !0*"3+" !*" !*-# !0",.3+" !90. !2.)).* !#,*3+"30-3"1 !".=0+2$' !-12$> !>3#"$*1 !0",.3+4
  76. 76. 4. does retweeting produce distinctly different accounts? 1. Select the top retweets per query. 2. Compare accounts.
  77. 77. 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)
  78. 78. #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)
  79. 79. 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)
  80. 80. conclusions. Two types of users Spaces of confrontation
  81. 81. controversy on twitter. Thank you. Research: Matteo Cernison, Simeona Petkova & Thomas Poell E-mail: Poell@uva.nl Wiki: http://wiki.digitalmethods.net/Dmi/SelfOrganizingContent
  82. 82. related search. Erik Borra, Docent, University of Amsterdam
  83. 83. 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
  84. 84. challenge. Can the related search option be turned into a research tool?
  85. 85. 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)
  86. 86. google examples. - "Global Warning" - "Global Warming Is An Idiot" - "Al Gore Isnt Real" Too much generativity and not enough selectivity.
  87. 87. strategies to counter act that. A high threshold of connectivity reveals when suggestions become inconsistent: No more path to known terms
  88. 88. !"#$%"&'7"$)*+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 !"(<$&$(;$'$ Polution !"(3''$6 Car !"(@.'.$=%7(?$0.= !"(?$0.= Polution !"(/0..%7 !=$07'(:4(!" Polution !"()44.%&' !"(-$,'.' !"(3''$6' Causes "7$&(-$,'.'(!" 344.%&'(:4(!" Causes & Effects Types of /&+0(!" !"(344.%&' Polution & Effects #$%&'(: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
  89. 89. related search as a re- search tool. organization of a content space query-design starting-points identification of programs / anti-programs classification and categorization
  90. 90. related search. Thank you. Research: Mathieu Jacomy, Matthieu Renault, Esther Weltevrede & Erik Borra E-mail: erik@digitalmethods.net Wiki: wiki.digitalmethods.net/Dmi/RelatedSearchAsQueryDesign
  91. 91. digital methods initiative summer school 2010. Thank you. E-mail: info@digitalmethods.net Wiki: http://summer2010.digitalmethods.net

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