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Mark Thomas Kennedy, 2010. All Rights Reserved.
Theory and Method for
Studying Meaning andRelated Social Structures
Introducing Association Engine (),
A Practical Tool for Relational Content Analysis
2010 Academy of Management Meetings | MontrealContent Analysis in Organizational Research:
Techniques and Applications
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8/2/2019 Theory and Method for Studying Meaning and Related Social Structures
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Mark Thomas Kennedy, 2010. All Rights Reserved.
Outline
Cool research questions
Meaning and social structure
New (research) realities
Key Inputs
Simple interface
Robust technologies
Community, standards matter!
Theory meetsMethod
Anatomyof a Project/Introducing
Relational ContentAnalysis Made Easy
Conclusion
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8/2/2019 Theory and Method for Studying Meaning and Related Social Structures
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Mark Thomas Kennedy, 2010. All Rights Reserved.
Cool topics being addressed by linkingmacro entities to patterns ofassociation
Grass-fed meat, dairyactivists found a collectionof codes seen as groundfor new identity, practices.1
WorkstationsMedia co-mentions of rivals revealcategory, prototype.2
Greenseen by finding
overlap in antagonistsassociation of attributes.3
Nanotechrepeatedpatterns of associationamong patent classes.4
Social and politicalmovements: How dofringe interests becomemainstream issues?
Markets: how doerstwhile misfits becomenew categories?
Corporate reputation:
how do criteria changeand emerge?
Fields, Forms &Genres: how do cross-category blends getnaturalized?
Published
In process
1. Weber et al. 2008
(ASQ)2. Kennedy 2008 (ASR)
3. Kennedy & Chok
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Mark Thomas Kennedy, 2010. All Rights Reserved.
Repeated patterns of association: awindow to dynamics of social realities
Meaning,Structure
Networks,Structure
Process,NetworkDynamics
Because meaning and structure are both seen inrelations among entities/ideas, they are duallyconstituted (Mohr and Duquenne 1997, Mohr 1998)
Recognition of social realities (sometimes alsolegitimate) emerges from repeated associations thatlink actors, entities or ideas (Emirbayer 1997, Tilly2008, Philips et al. 2000, Powell et al. 2005, Kennedy
2008)
One can trace the process of field-level change (Hardy& Maguire 2008) by studying the dynamics of networksof changing patterns of association between entities,
ideas, etc., (Owen-Smith & Powell 2008) and vice
But this type of work is laborious and riskybecause:1. the data is hard to get and code;2. finding relations requires RDB and trickyqueries;3. theory and method are new to most reviewers
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Mark Thomas Kennedy, 2010. All Rights Reserved.
Still hard, but the flood of web content =big opportunities for content analysis
Opportunity
Computer-assisted
Hundreds of thousands+
Also Blogs, RSS feeds
Commenters, too
Make-your-own!
Months?
Months, weeks, days,
Semantic networks
Before
Human coding
Hundreds
Media, PR
Reporters, Analysts
Published catalogs
Year or more
Usually years
Qualitative themes
Coding
Scale
Sources
Lag
Periods
Product
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Mark Thomas Kennedy, 2010. All Rights Reserved.
Of the styles of content analysis,this calls for relationalcontent analysis*
Semiotic
Semantic
Relational1
Statistical
Interpretation Explanation
FocalTer
m
Setsof
Terms
Em
piricalFocus
Styles of Content Analysis
Study Intent1. Carley and Palmquist 1992
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Interface (netbook example)
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Heres what a fuzzy ontology looks like
MTKcomputers
netbooka small, light-weight low cost laptop computer with long battery life; often used for Internet access and wireless
communicationnoun
lightweight, inexpensive, wireless,small, smaller than a laptoplong battery life
Dell, Sylvania, Acer, MSI, Lenovo, Samsung, HP, Toshiba, Asus|ASUSHP 2140 Mini-Note, Samsung NC10, Dell Inspiron Mini 9, MSI Wind, U100-279US, Asus Eee PC 1000HA, Lenovo
Ideapad S10, HP Mini 1000 XP Edition, Acer Aspire One AOA150-1126, Asus Eee PC 900HA, Sylvania GNET28001SO, Mesolaptop, mini-laptop, notebook, mini-notebook, sub-notebook, ultraportablemainframe, workstation, server
laptop, notebook, personal computer, PCsmartphone, tablet
personal computer
a small digital computer based on a microprocessor and designed to be used by one person at a timepersonal, small, microprocessor, desktop, speed, size, memory, storagePC, desktop
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8/2/2019 Theory and Method for Studying Meaning and Related Social Structures
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builds on robust open sourcelibraries for search, database, networkanalysis
Slicer& Dicer
Mention-Finder4
ConceptMapper
NetworkAnalyzer6
GUI(Front-End)
CorpusInput Files1
FuzzyOntology2
ConceptNetworks7
OutputCorpus6
LongitudinalDataset8
Inputs Outputs
isan association engine, a search utility that produces dynamic concept networks from 3 inputs:(1) a collection of relevant texts from LexisNexis, Factiva, or RSS/Atom feeds from blogs or websites (corpus);(2) a set of terms potentiallyrelevant to the concepts meaning (fuzzy ontology); and(3) rule(s) for when to treat co-mentions of these terms as links (association rules).
1. From any of the following:
LexisNexis (HTML), Factiva (XML), or the web (RSS/Atom feeds).
2. .fo file containing terms,definitions, synonyms, etc., orcommands for fetching themautomatically.
6. Corpus input files convertedand combined into one .c filefor later re-use as desired.
7. As Pajek .net file for analysis,visualization, exchange.
8. Output (.dat) file contains time-varying measures of conceptnetwork structure, position ofrelevant terms.
3. Builds on Lucene, an open source library (Java) used in a wide rangeof production search applications.
4. Builds on Lucene and MySQL, an open source implementation ofSQL. For table structure, see Functional Specification, section 2.4.
5. Builds on JUNG, an open source library (in Java) for social networkanalysis.
Notes
Modules
DB5
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Anatomy of a Project:3 Key Outputs
Visualize
Analyze
Explore* planned *
produces dynamic concept networks (DCNs),
Graph models of meaning and structure
Visualize / animate to observe changing patterns of
association over time
Get flat-file datasets for quantitative analysis (one rowper for each node-period observation)
Use DCNs to browse the corpus
Clicking nodes fetches texts that mention that term
Clicking a link fetches texts that co-mention thelinked terms
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Conclusion: Sober Excitement
Vision
Fitness
Or JustDeviation?
Enable study of difficult questions (dynamics), but cuttime, expense, riskincrease research productivity
Environmental factors giving content analysis new zip
Explosion of web contentripe for analysis Open source, esp. for search engine development
Advances in theory that link macro-level entities torecognition of patterns in lower-level relations
Take-off will also require: theory, identity, community,mutual recognition, complementary roles
Hazard-rate reg.+ institutions / ecology = take-off!
New content analysis + ______________ = ???
Other ideas?