ICA Slides

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2010 Conference of the International Communication Association

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ICA Slides

  1. 1. What is the problem? How can we deal with concept drift? Summary Extensional Mapping-Chains for studying Concept Drift in Political Ontologies Shenghui Wang1 Stefan Schlobach2 Janet Takens3 Wouter van Atteveldt3 1 The Network Institute 2 Department of Computer Science 3 Department of Communication Science Vrije Universiteit Amsterdam ICA 2010 Singapore
  2. 2. What is the problem? How can we deal with concept drift? Summary Content analysis in Communication Science Communication scientists study all sorts of media content related to human communication Content analysis based on the NET method concepts: political actors and issues relations: associations, opinions, or actions. Example Het Openbaar Ministerie (OM) wil de komende vier jaar mensen- handel uitroeien.
  3. 3. What is the problem? How can we deal with concept drift? Summary Content analysis in Communication Science Communication scientists study all sorts of media content related to human communication Content analysis based on the NET method concepts: political actors and issues relations: associations, opinions, or actions. Example Het Openbaar Ministerie (OM) wil de komende vier jaar mensen- handel uitroeien.
  4. 4. What is the problem? How can we deal with concept drift? Summary Content analysis in Communication Science Communication scientists study all sorts of media content related to human communication Content analysis based on the NET method concepts: political actors and issues relations: associations, opinions, or actions. Example Het Openbaar Ministerie (OM) wil de komende vier jaar mensen- handel uitroeien. -1 om human trafficking
  5. 5. What is the problem? How can we deal with concept drift? Summary Semantic network analysis 2271 1067 1388 740 1373 2127 2467 1268 2351 907 1223 1739 1708 2516 1706 2393 2438 1721 1077 1052 2323 1234 1034 2394 964 1275 2120 1936 1059 1045 2221 2124 2753 2171 2653 752 2655 2054 856 693 1608 341 2647 1011 2806 1145 1625 2076 648 1386 1233 1545 329 480 361 475 845 1906 2259 883 1439 2090 1474 1332 2002 2377 1306 2077 548 654 2696 2606 2492 1635 2471 484 956 889 2199 1198 623 2614 2573 545 1409 1259 2251 1940 2751 539 1827 870 2186 2151 2423 464 1097 1841 2070 1073 1932 438 2403
  6. 6. What is the problem? How can we deal with concept drift? Summary Network-based communication science study What information can we extract from these networks? Politicians are networking Politics is perceived by citizens via media Media study by semantic network analysis Who is determining the subjects? Who is teaming up? Who is more credible? Who owns which topic?
  7. 7. What is the problem? How can we deal with concept drift? Summary Before network analysis We first need to build the networks! Requires: large corpora with annotated textual content Manual coding against coding books (ontologies) Automated content analysis in progress
  8. 8. What is the problem? How can we deal with concept drift? Summary Before network analysis We first need to build the networks! Requires: large corpora with annotated textual content Manual coding against coding books (ontologies) Automated content analysis in progress
  9. 9. What is the problem? How can we deal with concept drift? Summary What is the problem? Problems with constructing annotated content Data from different time periods or genres Coded by different teams at different moments Manifesto Research Group: 25 countries, from 1945 to 2006 Comparative Policy Agendas project: media content, manifestos, legislative texts, government press statements, etc. Election campaign coverage from 1994 to 2006
  10. 10. What is the problem? How can we deal with concept drift? Summary What are the challenges? Interoperability problem while sharing information Different teams use different code books Example illegal immigration labour migrants Different coding books should be merged or at least connected Not the focus of this paper
  11. 11. What is the problem? How can we deal with concept drift? Summary What are the challenges? Interoperability problem while sharing information Different teams use different code books Example illegal immigration labour migrants Different coding books should be merged or at least connected Not the focus of this paper
  12. 12. What is the problem? How can we deal with concept drift? Summary What are the challenges? Interoperability problem while sharing information Different teams use different code books Example illegal immigration labour migrants Different coding books should be merged or at least connected Not the focus of this paper
  13. 13. What is the problem? How can we deal with concept drift? Summary Follow the Fashion?
  14. 14. What is the problem? How can we deal with concept drift? Summary Women’s role? Suffragettes said that women’s role in society is unacceptable Pope says that women’s role in society is unacceptable
  15. 15. What is the problem? How can we deal with concept drift? Summary Concept drift Our problem: Concept drift Meaning of concepts changes over time Analysis based on evolving concepts must consider temporal locality Study concept drift itself is useful
  16. 16. What is the problem? How can we deal with concept drift? Summary Datasets Five political ontologies which were used to annotate newspaper articles 23 639 manually annotated newspaper articles during five recent Dutch national election campaigns There even exist manual mappings but most of them are lexically very similar
  17. 17. What is the problem? How can we deal with concept drift? Summary Detecting concept drift We use extensional mapping techniques Consider concepts at different time to be different concepts Use extensional method to detect the links between concepts at different time Assumption: similar sentences should be coded with similar concepts, therefore, similar concepts should have similar extension.
  18. 18. What is the problem? How can we deal with concept drift? Summary Representing concept drift using mapping chains
  19. 19. What is the problem? How can we deal with concept drift? Summary Evaluating concept drift What can we learn from those chains? Do they agree with the political reality? Do they tell us something we do not noticed before? Are some concepts more stable/unstable than others? Quantitative evaluation is interesting, but qualitative analysis seems to tell us something too.
  20. 20. What is the problem? How can we deal with concept drift? Summary Qualitative analysis of mapping chains Association vs. similarity Early erroneous associations can turn large parts of the analysis practically useless.
  21. 21. What is the problem? How can we deal with concept drift? Summary Qualitative analysis of mapping chains Association vs. similarity Early erroneous associations can turn large parts of the analysis practically useless.
  22. 22. What is the problem? How can we deal with concept drift? Summary “productiviteit” (Productivity) 06_economic growth 0.0880 03_economische groei 0.0315 0.0569 06_begroting 0.0327 0.0499 0.0657 02_economische groei 03_financieringstekort 0.0336 06_bezuinigingen 0.0387 94_productiviteit 98_welvaart valence 0.0587 02_welvaart 0.0361 0.1505 03_spaarloon 06_spaarloon 0.0518 06_levensloopregeling “euthanasie” (Euthanasia) 0.1789 06_gay marriage 03_euthanasie 0.1704 0.2999 0.3491 06_abortion 0.2519 02_euthanasie 03_homohuwelijk 0.1883 0.1057 06_verbetering communicatie overheid burger 0.0165 0.2185 03_milieuactivist 0.0425 0.0768 06_criminelen 98_oeuthanasie 02_milieuactivist 0.0507 0.0310 0.2636 03_justitie 0.0291 06_asielzoekers 94_euthanasie 0.0457 06_gratis schoolboeken 0.0441 0.1117 03_referendum eu 0.0313 0.1016 98_hreferendum 02_referendum 0.0432 06_referendum 0.0571 03_referendum 0.0454 0.0882 06_burgerinitiatief 06_werknemers 0.0548 0.0293 02_cdavvdlpf 03_zondagsrust 0.0398 0.0257 06_sunday rest 0.0511 03_scholieren 06_leerlingen 0.0286 06_education
  23. 23. What is the problem? How can we deal with concept drift? Summary If we know two end-point concepts have the same meaning Kite-shaped chains 02_mensenrechten 98_avluchtelingen 02_jusititie 03_politie 02_criminaliteit 03_justitie 98_rcriminaliteit 02_drugkoeriers 02_cellentekort 03_criminaliteit 94_asielzoekers 98_kabinet kokmierlods 02_bedrijfsleven 02_democratie 98_asielzoekers 02_buitenlanders 03_asielzoekers 06_asielzoekers 98_okerken 02_instroom beperking 03_opvang illegalen 02_asielzoekers 03_vluchtelingen 03_illegalen
  24. 24. What is the problem? How can we deal with concept drift? Summary “christelijken” (Christians) 98_oabortus 02_normen waarden 94_christelijken 03_multiculturele samenleving 06_christenen 98_ochristelijk christenen 02_multiculturele samenleving “asielzoekers” (Asylum seeker) 02_mensenrechten 98_avluchtelingen 02_jusititie 03_politie 02_criminaliteit 03_justitie 98_rcriminaliteit 02_drugkoeriers 02_cellentekort 03_criminaliteit 94_asielzoekers 98_kabinet kokmierlods 02_bedrijfsleven 02_democratie 98_asielzoekers 02_buitenlanders 03_asielzoekers 06_asielzoekers 98_okerken 02_instroom beperking 03_opvang illegalen 02_asielzoekers 03_vluchtelingen 03_illegalen
  25. 25. What is the problem? How can we deal with concept drift? Summary Summary By looking at extensions of concepts, we can detect concept drift Domain experts found that the detected concept drift makes sense Automated matching techniques can help domain experts to find hidden links between concepts More work needs to be done

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