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USING AUTOMATED CODING & SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXTS A METHODOLOGICAL WORKSHOP Christian Baden LMU.

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Presentation on theme: "USING AUTOMATED CODING & SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXTS A METHODOLOGICAL WORKSHOP Christian Baden LMU."— Presentation transcript:

1 USING AUTOMATED CODING & SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXTS A METHODOLOGICAL WORKSHOP Christian Baden LMU Munich Germany Wouter van Atteveldt VU Amsterdam Netherlands &

2 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 AGENDA for TODAY 09:30 – 11:00Vocabulary, Grammar, and Semantic Networks Coffee Break 11:30 – 13:15Discourse Analysis as Semantic Network Analysis 13:15 – 13:30Questions & Answers Lunch Break 14:30 – 15:30Hands-on session (Computer Lab, optional)

3 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 LOGIC OF QUANTITATIVE DISCOURSE ANALYSIS Isn’t Discourse Analysis (DA) qualitative?  construction of subtle meaning  through the use of language  in recurrent, regular ways  to reflect and constitute social and power relations  and reflecting the underlying social processes of their emergence, codification, and contestation

4 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 LOGIC OF QUANTITATIVE DISCOURSE ANALYSIS Isn’t Discourse Analysis (DA) qualitative?  construction of subtle meaning  through the use of language  in recurrent, regular ways  to reflect and constitute social and power relations  and reflecting the underlying social processes of their emergence, codification, and contestation defining how ideas are  in/excluded  labeled  connected  contextualized defining how ideas are  in/excluded  labeled  connected  contextualized comparing across  documents  situations  authors/groups  thematic domains  etc. comparing across  documents  situations  authors/groups  thematic domains  etc. tracing changes  over time  between groups  across contexts  etc. tracing changes  over time  between groups  across contexts  etc. interpretation in a  culturally informed  theoretically informed  critical manner interpretation in a  culturally informed  theoretically informed  critical manner

5 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 LOGIC OF QUANTITATIVE DISCOURSE ANALYSIS Isn’t Discourse Analysis (DA) qualitative?  construction of subtle meaning  through the use of language  in recurrent, regular ways  to reflect and constitute social and power relations  and reflecting the underlying social processes of their emergence, codification, and contestation search for regularities search for regularities inductive analysis of language use interpretative /critical latent structures wide, large, & deep data wide, large, & deep data

6 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 LOGIC OF QUANTITATIVE DISCOURSE ANALYSIS Isn’t Discourse Analysis qualitative? Quantitative Discourse Analysis (qDA)… …accesses language use at a nuclear, lowest possible level of abstraction …searches for recurrent, latent patterns in language use …within large scale, diverse and detailed discourse …to create a representation that can be interpreted with regard to the detected patterns’ significance for constructing social reality

7 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 LOGIC OF QUANTITATIVE DISCOURSE ANALYSIS DA/CDAqDA language useinductive, fully flexibleinductive, some categorization necessary at micro level latent patternsby qualitative analysisby detection of covariance coherenceby qualitative analysis of individual texts algorithmic, theory-informed, manually validated aggregationvariable, usually semantic aggregation preserving texts across texts, focus on concepts/ relations, otherwise variable coveragelimited Nvery large N possible comprehensive, culturally sensitive, validation in individual texts, good recall, close link to authors/situations comprehensive, culturally sensitive, validation in individual texts, good recall, close link to authors/situations validation in large number of texts, rule-based detection of latent patterns, precision/reliability, highly flexible slicing/aggregation validation in large number of texts, rule-based detection of latent patterns, precision/reliability, highly flexible slicing/aggregation some possible aggregation fallacies, reduced situation context, final interpretation remains manual some possible aggregation fallacies, reduced situation context, final interpretation remains manual limited coverage, laborious change of perspective, latent patterns derived by interpretation limited coverage, laborious change of perspective, latent patterns derived by interpretation

8 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 PREPARING qDA Three main preparatory steps are crucial for high quality in qDA: I.capturing conceptual meaning of manifest language use in high detail II.appropriate definition of the semantic context of measured concepts III.relevant selection of (preferably many) discourse texts

9 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 PREPARING qDA I.capturing conceptual meaning of manifest language use in high detail inductive pilot study necessary to develop ontology:  detect & validate subtle variations of language use  as-exhaustive-as-possible capturing of meaning-carrying expressions  “nuclear” coding strategy: relatively close to lexical indicators  group codes only if equivalent meaning can be assumed  distinguish polysemic indicators  iterative construction and validation of very! long ontologies

10 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 PREPARING qDA II.appropriate definition of the semantic context of measured concepts When does it make sense to conclude that one concept occurs in another’s context (i.e., a collocation is meaningful)?  careful, theory-informed modeling of context structure Baden, 2010: context structure based on discourse processing theory:  short distances, sensitive to grammatical boundaries  reflection of textual meso- and macrostructures (e.g., titles/headlines, enumeration topics, etc.) and meta-information (e.g., authors/sources) Motta & Baden, 2013:  in addition, temporal modeling of decaying memory Every unitization strategy has its weaknesses:  formal units (sentence, paragraph, text, issue)  social units (author, group, society)  temporal units (hour, day, week, month)  etc. Every unitization strategy has its weaknesses:  formal units (sentence, paragraph, text, issue)  social units (author, group, society)  temporal units (hour, day, week, month)  etc. Indien de Europese Raad (met gewone meerderheid) besluit om de voorgestelde wijzigingen te willen bespreken xxcomma wordt daarvoor in beginsel een Conventie bijeengeroepen (tweede lid) xxdot xxx xxx De regering is verheugd dat op deze wijze de Conventiemethode is geïnstitutionaliseerd xxdot xxx xxx Evenals in artikel 48 van het EU-Verdrag xxcomma dient de Europese Raad echter alvorens een dergelijk besluit te kunnen nemen het Europees Parlement en de Commissie te raadplegen xxdot xxx xxx Ook de Europese Centrale Bank moet worden geraadpleegd indien institutionele wijzigingen op monetair gebied worden voorgesteld xxdot xxx xxx xxbreak xxx xxx xxx xxx xxbreak xxx xxx xxx xxx Het is vervolgens aan de Conventie xxhyphen die naast regerings-vertegenwoordigers ook bestaat uit vertegenwoordigers van nationale parlementen xxcomma het Europees Parlement en de Commissie xxhyphen om de voorgestelde wijzigingen te beoordelen en bij consensus een aanbeveling te richten tot de daaropvolgende IGC xxdot xxx xxx xxbreak xxx xxx xxx xxx xxbreak xxx xxx xxx xxx De Europese Raad kan echter ook besluiten geen Conventie bijeen te roepen xxcomma maar de wijzigingsvoorstellen direct aan een uit regeringsvertegen-woordigers samengestelde IGC voor te leggen (derde lid) xxdot xxx xxx Dit is echter alleen mogelijk indien de reikwijdte

11 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 PREPARING qDA III.relevant selection of (preferably many) discourse texts Basically, wide is good and “cost-free”. BUT different text forms may imply different context structures, different regularities, different conventions in language use, etc.  may require adjustment of measurement tools  may require separate analysis/cautious comparative analysis  Keep identifying & meta information on texts behind the analysis!

12 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 SEMANTIC NETWORK “ANALYSIS” IN qDA A Semantic Network is a formal representation of the text  NOT (yet) a specific analysis Sematic Networks…  represent concepts as nodes and associations as links  abstract/aggregate across many texts  maintain the full textual context structure (as far as coded)  allow a range of zooming operations  allow the identification of patterns (latent/manifest; absence/presence)  SN representations allow inferences from patterns rather than instances

13 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 SEMANTIC NETWORK “ANALYSIS” IN qDA A Semantic Network is a formal representation of the text which can focus on different aspects and patterns:  salience of concepts, presence of concepts, functional role of concepts  strength of relations, presence of relations, context-embeddedness of relations, … Frequency is often problematic as an indicator, due to  natural frequencies in language use  text-(type-)specific properties  uneven text frequencies, etc. Different kinds of association measures focus on different things:  co-occurrence frequency: absolute salience  asymmetric association (e.g., P(A|B)): association chains/attribution  symmetric association (e.g., covariance, cosine): coherence relations  binary codes (e.g., everything significant): context patterns Frequency is often problematic as an indicator, due to  natural frequencies in language use  text-(type-)specific properties  uneven text frequencies, etc. Different kinds of association measures focus on different things:  co-occurrence frequency: absolute salience  asymmetric association (e.g., P(A|B)): association chains/attribution  symmetric association (e.g., covariance, cosine): coherence relations  binary codes (e.g., everything significant): context patterns

14 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 SEMANTIC NETWORK “ANALYSIS” IN qDA A Semantic Network is a formal representation of the text that can be accessed on four-plus levels of abstraction…:  network level: properties of the discourse  subnet level: cohesive patterns/structures within discourse  dyad level: associative relations  node level: properties/roles of specific concepts/ideas  (attribute level: bringing meta information back in)  components, size, density, diameter  clustering coefficient, modularity  maximum/average centrality  etc.  components, size, density, diameter  clustering coefficient, modularity  maximum/average centrality  etc.  association strength/directionality  significance  association strength/directionality  significance  (in-/out-)degrees  centrality, betweenness  structural equivalence  affiliation  (in-/out-)degrees  centrality, betweenness  structural equivalence  affiliation  What kinds of nodes…  Nodes from what kinds of texts/authors…  within/between subsample relations  comparative, dynamic, etc. analysis  What kinds of nodes…  Nodes from what kinds of texts/authors…  within/between subsample relations  comparative, dynamic, etc. analysis

15 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 COHERENCE & FRAMES How can one find meso-level cohesive, coherent semantic structures?  how is coherence reflected in association patterns within a network? Direct connectedness?  journalistic balance norm: contrasting views often juxtaposed  synonyms rarely co-occur, the most coherent concepts usually have a step-distance 2

16 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 COHERENCE & FRAMES How can one find meso-level cohesive, coherent semantic structures?  how is coherence reflected in association patterns within a network? Direct connectedness? Not good. Structural equivalence?  concepts that relate to the same set of third concepts and none else typically perform equivalent functions in discourse  they may still convey quite different meanings

17 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 COHERENCE & FRAMES How can one find meso-level cohesive, coherent semantic structures?  how is coherence reflected in association patterns within a network? Direct connectedness? Not good. Structural equivalence? Good for some questions, not others. Common context?  pairs of concepts associated with the same third concepts, which are also associated with one another, are usually coherent.  My strategy: 2-Clans (subnets where no node is further than 2 steps away from all other nodes) & 4-Cliques (fully connected networks of 4)

18 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 Wouter van Atteveldt VU Amsterdam Wouter van Atteveldt VU Amsterdam Collocations in the discourse of GroenLinks data reduction: associations significantly more frequent than expected (p <.001) REFERENDUM Baden, 2010

19 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 data reduction: associations significantly more frequent than expected (p <.001) data weighting: context density as 4- clique membership count REFERENDUM Baden, 2010

20 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 data weighting: context density as 4- clique membership count data clustering: identification of cohesive structures based on density REFERENDUM Baden, 2010

21 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 data clustering: identification of cohesive structures based on density data clean-up: removal of inter-cluster- associations below a minimum weight of 5 REFERENDUM Baden, 2010

22 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 data clean-up: removal of inter-cluster- associations below a minimum weight of 5 REFERENDUM Baden, 2010

23 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 SEMANTIC NETWORK ANALYSIS IN qDA A Semantic Network is a formal representation of the text That allow a wide range of analytic options…:  visual/manual interpretation  of small networks or aggregated (shrunk) networks  of induced small sub-networks  formal pattern-finding operations, grouping, (dis-)aggregation  network-analytic grouping algorithms  groupings based on meta-information (authors, phases, etc.)  fully mathematical analytic procedures  network metrics (e.g., centrality, clustering, modularity)  statistical dimension-reduction/classification (e.g., HCA, FA, MDS)  comparative/dynamic analysis: Jaccard, QAP, DNA, EFA, …  “significance” analysis using p* (ERGM) models

24 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 METAPHORS, PHASE I Baden & Schultz, 2013

25 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 METAPHORS, PHASE II Baden & Schultz, 2013

26 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 METAPHORS, PHASE III Baden & Schultz, 2013

27 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 METAPHORS, PHASE III Baden & Schultz, 2013

28 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 REFERENDUM Baden, 2010

29 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 comparative perspective: cluster context of ‘decide’ for GroenLinks, SP, & VVD democratic representation of EU citizens democracy must remain on national level less intrans- parency, more control power balance between big & small states EU Commission EU Council levels of decision making & EU Parliament REFERENDUM Baden, 2010

30 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 REFERENDUM, NEWS VS. VOTERS Baden, 2010

31 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 REFERENDUM, NEWS VS. VOTERS Baden, 2010 Dependent network:Total discussions Phase betaSig. I Brabants Dagblad0,0110,01 Dagblad van het Noorden-0,0090 NRC Handelsblad0,0100,02 Telegraaf Trouw II Algemeen Dagblad-0,0120 Dagblad van het Noorden-0,0060,04 NRC Handelsblad Telegraaf Trouw Volkskrant0,0080,03 III Dagblad van het Noorden0,0080,03 Metro-0,0030,01 Telegraaf Trouw IV Dagblad van het Noorden-0,0080,01 Metro-0,0050 Telegraaf-0,0070,01 V Algemeen Dagblad0,0130,01 Brabants Dagblad NRC Handelsblad0,0160 Trouw Volkskrant0,0180 V (TV) Barend & van Dorp0,0140 Buitenhof0,0120,02 NOS Journaal0,0230 NOVA / Den Haag vandaag0,0160,01 V (Yes Camp) GroenLinks0,0180 Government Partij van de Arbeid PvdA0,0140 V (No Camp) Comité Grondwet Nee0,0160 ChristenUnie Lijst Pim Fortuyn LPF SGP-0,0050,01 Socialistische Partij SP0,0090,04 Groep Wilders VI Algemeen Dagblad Dagblad van het Noorden Metro-0,0070,01 Telegraaf Trouw Volkskrant VII Algemeen Dagblad-0,0040,03 Brabants Dagblad-0,0080,01 Metro Telegraaf Volkskrant-0,0080,02 R squared0,009 0 Adj. R squared0,008 N124,256

32 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 REFERENDUM, FRAME TRANSFORMATION Motta & Baden, 2013 svg

33 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 FINANCIAL CRISIS, GREEK & GERMAN DEBATE Baden, Motta, & Dimitrakopoulou, 2013 Factor 1 (dominant Frame) X: Germany X: Germany Y: Greece Y: Greece svg

34 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 FINANCIAL CRISIS, GREEK & GERMAN DEBATE Baden, Motta, & Dimitrakopoulou, 2013 Factors 1-5 Factors 1-5

35 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 FINANCIAL CRISIS, GREEK & GERMAN DEBATE Baden, Motta, & Dimitrakopoulou, 2013 Germany Greece Y: factor 1 (dominant frame) Y: factor 1 (dominant frame) strikes & parliament hearing Germany against rescue plans referendum & collapse of interim government Germany (t-1) predicts Greece Greece (t-1) predicts Germany

36 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 QUALITY ASSESSMENT OF qDA The quality of qDA depends mostly on the justification and careful implementation of a range of consequential decisions. pre-network-construction decisions:  nodes (semantic equivalence, grouping rules, exhaustiveness)  relations (quality, categorical/strength differentiation)  texts/units (context structure, treatment of distinct texts)  time/phases/authors/groups (stability of discourse)  measures (frequency, other properties) post-construction decisions:  reduction (what information is reduced as noise)  structures (what is considered a pattern)  choice of analytic approach

37 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 IN SUMMARY qDA’s main features are:  nuclear coding of concepts at lowest possible level of abstraction  theory-informed modeling of semantic context  algorithmic extraction of association patterns over very many texts  representation and further structuring as Semantic Network, which  retains the full measured context structure  can be flexibly structured, restructured and zoomed into/out of  can be analyzed qualitatively and quantitatively  qDA is preceded and (normally) succeeded by qualitative text analysis.  Unlike DA, qDA derives its patterns first and interpretations second.  Like DA, qDA builds inductively upon subtle variations in regular language use to express different semantic meaning.

38 USING AUTOMATED CODING AND SEMANTIC NETWORK ANALYSIS TO INVESTIGATE MEANING IN LARGE SCALE DISCOURSE TEXT CHRISTIAN BADEN WOUTER VAN ATTEVELDT Hebrew University Jerusalem 15 & 17 July 2013 that‘s all for now, thanks for your attention! lmu.de & vu.nl


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