Computer	
  Science	
  and	
  Journalism	
  
Two	
  great	
  tastes	
  that	
  taste	
  great	
  together	
  
	
  
Februar...
WORDS	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  vs.	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  NERDS	
  
ComputaHonal	
  Journalism:	
  DefiniHons	
  
“Broadly	
  defined,	
  it	
  can	
  involve	
  changing	
  how	
  
stories	
 ...
ComputaHonal	
  Journalism:	
  DefiniHons	
  
“Stories	
  will	
  emerge	
  from	
  stacks	
  of	
  financial	
  
disclosure...
CS	
  for	
  reporHng	
  
Data	
   ReporHng	
  
User	
  
Computer	
  
Science	
  
visualizaHon,	
  staHsHcs,	
  natural	
 ...
OpenLand	
  Data	
  Map,	
  JMSC	
  Data	
  Lab	
  
CS	
  for	
  presentaHon	
  
Data	
   ReporHng	
  
User	
  
CS	
  
CS	
  
visualizaHon,	
  interacHvity,	
  web	
  applica...
Graph	
  of	
  poliHcal	
  book	
  sales	
  during	
  2008	
  U.S.	
  elecHon,	
  by	
  orgnet.org	
  	
  
From	
  Amazon	...
Retweet	
  network	
  of	
  poliHcal	
  tweets.	
  	
  
From	
  Conover,	
  et.	
  al.,	
  Poli(cal	
  Polariza(on	
  on	
...
CS	
  for	
  filtering	
  
User	
  
Data	
  
ReporHng	
  
CS	
  
Data	
  
ReporHng	
  
CS	
  
Data	
  
ReporHng	
  
CS	
  
...
Memetracker	
  by	
  Leskovic,	
  Backstrom,	
  Kleinberg	
  	
  
CS	
  for	
  tracking	
  effects	
  
User	
  
Data	
  
ReporHng	
  
CS	
  
Data	
  
ReporHng	
  
CS	
  
Data	
  
ReporHng	
...
Four	
  Places	
  Journalism	
  Needs	
  CS	
  
	
  
ReporHng	
  
PresentaHon	
  
Filtering	
  
Tracking	
  
	
  
Natural	
  Language	
  
Processing	
  
Data	
  Science	
  
Sociology	
  
ArHficial	
  	
  
Intelligence	
  
CogniHve	
  Sci...
TruthTeller,	
  Washington	
  Post	
  
Sina	
  Weibo	
  Crypt,	
  JMSC	
  Data	
  Lab	
  
WORDS	
  and	
  NERDS	
  
Data	
  Journalism	
  Handbook	
  +	
  Computa(onal	
  Journalism	
  lectures	
  
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
Computer Science and Journalism: two great tastes that taste great together
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Computer Science and Journalism: two great tastes that taste great together

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Computer science and journalism are intersecting in surprising ways. Computational journalism combines classic journalistic values of storytelling and public accountability with techniques from computer science, statistics, the social sciences, and the digital humanities. This talk will be a lightning overview of the state of the art in this rapidly developing field, including work being done here at the Journalism and Media Studies Center at HKU.

For the full talk video and notes, see http://jmsc.hku.hk/courses/jmsc6041spring2013/

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Computer Science and Journalism: two great tastes that taste great together

  1. 1. Computer  Science  and  Journalism   Two  great  tastes  that  taste  great  together     February  4,  2013  
  2. 2. WORDS                          vs.                    NERDS  
  3. 3. ComputaHonal  Journalism:  DefiniHons   “Broadly  defined,  it  can  involve  changing  how   stories  are  discovered,  presented,  aggregated,   moneHzed,  and  archived.  ComputaHon  can   advance  journalism  by  drawing  on  innovaHons   in  topic  detecHon,  video  analysis,   personalizaHon,  aggregaHon,  visualizaHon,  and   sensemaking.”      -­‐  Cohen,  Hamilton,  Turner,  Computa(onal  Journalism  
  4. 4. ComputaHonal  Journalism:  DefiniHons   “Stories  will  emerge  from  stacks  of  financial   disclosure  forms,  court  records,  legislaHve  hearings,   officials'  calendars  or  meeHng  notes,  and   regulators'  email  messages  that  no  one  today  has   Hme  or  money  to  mine.  With  a  suite  of  reporHng   tools,  a  journalist  will  be  able  to  scan,  transcribe,   analyze,  and  visualize  the  paVerns  in  these   documents.”      -­‐  Cohen,  Hamilton,  Turner,  Computa(onal  Journalism  
  5. 5. CS  for  reporHng   Data   ReporHng   User   Computer   Science   visualizaHon,  staHsHcs,  natural  language  processing,  graph  theory  
  6. 6. OpenLand  Data  Map,  JMSC  Data  Lab  
  7. 7. CS  for  presentaHon   Data   ReporHng   User   CS   CS   visualizaHon,  interacHvity,  web  applicaHons,  user  interface  design  
  8. 8. Graph  of  poliHcal  book  sales  during  2008  U.S.  elecHon,  by  orgnet.org     From  Amazon  "users  who  bought  X  also  bought  Y"  data.    
  9. 9. Retweet  network  of  poliHcal  tweets.     From  Conover,  et.  al.,  Poli(cal  Polariza(on  on  Twi<er  
  10. 10. CS  for  filtering   User   Data   ReporHng   CS   Data   ReporHng   CS   Data   ReporHng   CS   Filtering   CS   CS   CS   CS   natural  language  processing,  machine  learning,  social  so`ware  
  11. 11. Memetracker  by  Leskovic,  Backstrom,  Kleinberg    
  12. 12. CS  for  tracking  effects   User   Data   ReporHng   CS   Data   ReporHng   CS   Data   ReporHng   CS   Filtering   CS   CS   CS   CS   Effects   CS   big  data,  visualizaHon,  natural  language  processing,  bioinformaHcs  
  13. 13. Four  Places  Journalism  Needs  CS     ReporHng   PresentaHon   Filtering   Tracking    
  14. 14. Natural  Language   Processing   Data  Science   Sociology   ArHficial     Intelligence   CogniHve  Science  StaHsHcs   Graph  Theory   Clustering   Text  Analysis   Filter  Design   Social  Network  Analysis   Knowledge  RepresentaHon   Drawing  Conclusions   InformaHon  Retrieval  
  15. 15. TruthTeller,  Washington  Post  
  16. 16. Sina  Weibo  Crypt,  JMSC  Data  Lab  
  17. 17. WORDS  and  NERDS  
  18. 18. Data  Journalism  Handbook  +  Computa(onal  Journalism  lectures  

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