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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 WELCOME TO THE WORKSHOP! Dr. Wouter van AtteveldtDr. Christian Baden VU University AmsterdamLMU Munich

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 AGENDA for TODAY 09:30 – 09:45Introduction 09:45 – 10:30Quantitative analysis of discourse 10:30 – 11:30Automatic & manual coding using AmCAT Coffee Break 12:00 – 13:00Analytic opportunities within the AmCAT framework 13:00 – 13:30Examples & Applications Lunch Break 14:30 – 15:30Hands-on session (Computer Lab, optional)

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 AGENDA for WEDNESDAY 09:30 – 11:00Vocabulary, Grammar, and Semantic Networks 11:00 – 11:30Discourse Analysis as Semantic Network Analysis Coffee Break 12:00 – 12:45Context, Patterns, and Associative Coherence 12:45 – 13:15Analytic opportunities beyond the AmCAT framework 13:15 – 13:30Questions & Answers Lunch Break 14:30 – 15:30Hands-on session (Computer Lab, optional)

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 AUTOMATED CONTENT ANALYSIS Content Analysis as rule-bound categorization of semantic contents in text Codebooks contain all categories identify the rules that decide when a category must be coded, using… IF – THEN statements lists of indicators disambiguation criteria (typical examples) (logics) (etc.) A perfect codebook achieves that even the most ignorant coder arrives at precisely the same coding decisions by following the rules.

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 AUTOMATED CONTENT ANALYSIS Content Analysis as rule-bound categorization of semantic contents in text Ontologies contain all categories identify the rules that decide when a category must be coded, using… IF – THEN statements lists of indicators disambiguation criteria An ontology necessarily assumes that it actually has to work with this most ignorant coder (a computer). So in essence, an ontology is a codebook that has such precise rules that it leaves no interpretative decision to the coder

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 AUTOMATED CONTENT ANALYSIS Codebooks can be used to code very different things: Presence of specific actors/objects Presence of specific issues/topics Presence of evaluative statements/expressions Association of specific attributes with actors/objects or issues/topics Association of specific evaluations with actors/objects or issues/topics Expression of specific actions Expression of specific kinds of relations between actors/objects Expression of specific kinds of relations between issues/topics Qualification of specific actions and kinds of relations descriptors level of abstraction denotation connotation ironic/ figurative use ironic/ figurative use explicit/ Implicit association explicit/ implicit/ pragmatic actions relation types intensity, qualifiers

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

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

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 USING LANGUAGE AS AN INDICATOR Access to language depends on kind of question: How would I see in the use of language whether X is the case? "usual" contents are conceptual: objects/actors, attributes, actions etc. but not all contents are conceptual: think also of "unusual" markers: tense (e.g., we will) conjunctions (e.g., without) negations/qualifications (e.g., not a good idea) grammatical functions (e.g., objects, subjects) nearby markers (e.g., however) text structures (e.g., interview turns, subheadings)...

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 USING LANGUAGE AS AN INDICATOR What exactly in language use is indicative? Presence of X: frequencies, or positions, or qualifiers, or… Co-occurrences: within what, how far, how qualified, etc… Semantic relations: Explicit, implicit, implicated, or… Evaluations: where, by whom, etc.?; list, balance, order, or…

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 USING LANGUAGE AS AN INDICATOR What role does context play for my question? irrelevant (e.g., pure visibility over time) instrumental (e.g., for disambiguation/identification) information (e.g., focus on association patterns) Think of different kinds of contexts: immediate contexts (e.g., same sentence, word distance) formal contexts (e.g., same text, same issue) temporal context (e.g., same day, same phase) topical contexts (e.g., other statements on same topic) actor contexts (e.g., other statements by same actor) genetic contexts (e.g., knowledge available when something was said) etc.

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 SUMMARY: AUTOMATED CONTENT ANALYSIS… …is a form of text analysis that requires a lot of precision in preparing the coding instructions, and therefore depends crucially on: a question that determines the kinds of contents needed to answer it knowledge about the use of language as indicator dictionary knowledge often insufficient qualitative pilot studies often useful a lot of diligence to make sure all of the right indicators, and only the right indicators are considered in the ontology Furthermore, it is helpful to have: order/conventionality in language use good familiarity with the language coded whenever post-coding computations are needed: scale

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 …any questions so far? Wouter takes it from here… !?

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 APPLICATIONS & EXAMPLES Van Atteveldt, 2008 Document frequency: How much publication is there about…? Simple salience analysis/Issue careers Identifying events driving news coverage Comparing different outlets/subdiscourses Document frequency: How much publication is there about…? Simple salience analysis/Issue careers Identifying events driving news coverage Comparing different outlets/subdiscourses

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 APPLICATIONS & EXAMPLES Van Atteveldt, Ruigrok, Schlobach, van Harmelen, 2008 Document selection: Which discourse texts do I want to look at? validating qualitative text analysis identifying texts that differ systematically with regard to the use of certain terms identifying prototypical texts for some kind of repertoires identifying the first texts when something came up in a debate Document selection: Which discourse texts do I want to look at? validating qualitative text analysis identifying texts that differ systematically with regard to the use of certain terms identifying prototypical texts for some kind of repertoires identifying the first texts when something came up in a debate

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 APPLICATIONS & EXAMPLES Document scaling/grouping/categorization: What kinds of documents are there? Based on meta-data Based on content data Document scaling/grouping/categorization: What kinds of documents are there? Based on meta-data Based on content data

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 APPLICATIONS & EXAMPLES Balmas & Sheafer, 2013Kleinnijenhuis, Schultz, Oegema, & van Atteveldt, 2013 Concept frequencies: How much talk is there about…? Identifying issue careers, new topics, etc. Detecting biases in using concepts, quoting actors/sources, etc. Assessing the relative importance of concepts, actors, etc. in the news Concept frequencies: How much talk is there about…? Identifying issue careers, new topics, etc. Detecting biases in using concepts, quoting actors/sources, etc. Assessing the relative importance of concepts, actors, etc. in the news

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 APPLICATIONS & EXAMPLES Van Nooije, 2010 Van Atteveldt, 2008 Bag-of-words frequencies Comparing the prevalence of certain kinds of words/language styles/types of actors/thematic domains/etc. Wider notion of issue careers Bag-of-words frequencies Comparing the prevalence of certain kinds of words/language styles/types of actors/thematic domains/etc. Wider notion of issue careers

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 APPLICATIONS & EXAMPLES Cooccurrences & Associations Attribution, 2 nd level agenda setting, etc.: How frequently & how strongly are concepts associated? Association measures: Uni- /bidirectional associations Cooccurrences & Associations Attribution, 2 nd level agenda setting, etc.: How frequently & how strongly are concepts associated? Association measures: Uni- /bidirectional associations Van Atteveldt, Ruigrok, Schlobach, van Harmelen, 2008

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 APPLICATIONS & EXAMPLES Listing Concordances: What are the contexts wherein a specific concept or word occurs? Useful for discourse/framing analysis and the construction of disambiguation rules Listing Concordances: What are the contexts wherein a specific concept or word occurs? Useful for discourse/framing analysis and the construction of disambiguation rules

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 APPLICATIONS & EXAMPLES Sheafer, Shenhav, Takens, & van Atteveldt, 2013 Explaining Association strengths Comparing association strengths across discourses/corpora Correlating association strengths with third variables Explaining Association strengths Comparing association strengths across discourses/corpora Correlating association strengths with third variables

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 APPLICATIONS & EXAMPLES Schultz, Kleinnijenhuis, Oegema, Utz, & van Atteveldt, 2012 Van Atteveldt, 2008 Semantic Networks Detecting associations between larger sets of concepts (more tomorrow) Semantic Networks Detecting associations between larger sets of concepts (more tomorrow)

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 APPLICATIONS & EXAMPLES Van Atteveldt, Ruigrok, Schlobach, van Harmelen, 2008 Evaluative Statements & Communicative relations Rating the evaluative tendency of texts and statements Reconstructing Actor relations Evaluative Statements & Communicative relations Rating the evaluative tendency of texts and statements Reconstructing Actor relations

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 thats all for today, see you on wednesday! lmu.de & vu.nl


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