Big Data and Formal Methods of Cultural Analysis. Slides
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1 Big Data and Formal Methods of Cultural Analysis John Mohr UC-Santa Barbara Talk presented at the Center for Information, Technology & Society, University of California, Santa Barbara (10/15/13) Slides 1 1
2 The greatest enterprise of the mind has always been and always will be the attempted linkage of the sciences and the humanities. (E. O. Wilson, Consilience, 1998, p. 8) 2
3 I. Big Data and Social Science. 3
4 I. Big Data and Social Science: A. The Biggest thing yet in social science. Why? B. Social Science Lags Behind Natural Science. Why? Size of workforce, $ investment? Humans make bad (non-compliant) research subjects Human action, human institutions built out of meaning How do you measure meaning? The Biggest Problem... 4
5 I. Big Data and Social Science: The Biggest Problem...Getting good data. Limited from the beginning (origins in state statistics) and so we re used to it. For the complexities of consciousness we have surveys Leads to lack of common data core, data sharing, scientific theorizing across disciplines (even across sub-disciplines) Sociology Middle-Range theory (Robert K. Merton). 5
6 I. Big Data and Social Science: Big Data holds out the promise of changing this. Twitter, Face-Book, Wikipedia, Blogs, , text archives, etc. People make data as they make life (solves the noncompliance problem) People deposit traces of meaning along with traces of action (solves the meaning measurement problem) Now we just need to train social scientists to get access to Big Data so that it can be analyzed 6
7 Ambuj Singh, Divy Agrawal, John Mohr, Stephen Proulx and Subhash Suri (PI s) Communication, Computer Science, Ecology, Evolution and Marine Biology (EEMB), Electrical and Computer Engineering (EEC), Geography, Mechanical Engineering, Sociology 7
8 I. Big Data and Social Science: Doesn t solve the meaning measurement analysis problem, here (thanks to under-development of science and unavailability of data) we still have a long ways to go. 8
9 9
10 II. Formal Analysis and the Sociology of Culture 10
11 11
12 #I 111 Charity Fund of the Chamber of Commerce #D 1883 #J 42 #W distressed merchants who shall have been members of the Chamber in good repute in the City of New York and whose misfortunes were not the result of any dishonorable transactions 12
13 13
14 14
15 #I 681 New York Juvenile Asylum #L 176th Street and 10th Avenue #D 1851 #J 23 #WP truant children of both sexes residents of city committed by Magistrate 7 <=AGE<= 14 #WP truant children of both sexes residents of the city surrendered by parents or guardians 7 <=AGE<= 14 #WP disobedient children of both sexes residents of the city committed by Magistrate 7 <=AGE<= 14 #WP disobedient Children of both sexes residents of the city surrendered by parents or guardians 7 <=AGE<= 14 #J 53 #WP friendless children #WP surrendered children 15
16 The Duality of Culture & Practice: An Example. Focus on Ideas (Culture) & Practice. Illustrate they are coconstitutive Theory & Society, 1997 Vol. 26 (2/3):
17 Example: What is the Meaning of the term Indigent? Destitution? Distress? Deservingness or Worthyness? Being described as Fallen, Homeless, Misfortunate, Needy, or Poor? Look to Practical Implications: Given Advice? Food? Money? Work? Investigated or put in the Poorhouse? references to these Categories in NYCCD We look for logical possibility (binary yes/no) 17
18 Mohr & Duquenne Cultural Distinction x Practice, 1888: What goes with what? 18
19 Cultural Distinction x Poverty Practice, 1888: What is a subset of what? (And, vice-versa) Mohr & Duquenne 19
20 Cultural Distinction x Poverty Practice, 1888: Mohr & Duquenne What are the structural articulations that define each other? 20
21 Split: whenever a pair category/practice (c/p) is such that both are "irreducible" and that p is the lowest practice not below c while c is the highest category not above p in the lattice, the pair c/p is said to be "perspective." Example paidwk/needy 21
22 22
23 g:give$ f:food 23
24 24
25 g:give$ f:food 25
26 Cultural Distinction x Poverty Practice: A Focus on Splits in Lattice Structures as Critical Markers for textual interpretation. Mohr & Duquenne 26
27 Cultural Distinction x Poverty Practice in 1917: A New Institutional Logic stabilizes. Mohr & Duquenne 27
28 III. More examples of Formal Analysis and the Sociology of Culture 28
29 D. Duality Analysis - Examples of Applying Duality Analysis to Culture Charles Tilly ( ) 1997 Parliamentarization of Popular Contention in Great Britain, Theory & Society 26 (2/3): Uses Blockmodels to Analyze Duality of Identities & Actions (in texts). 29
30 D. Duality Analysis - Examples of Applying Duality Analysis to Culture. Ann Mische & Pip Pattison Lattice analysis groups & individual ideologies Poetics, 2000 Vol. 27 (2/3):
31 D. Duality Analysis - Examples of Applying Duality Analysis to Culture Ron Breiger examines the duality of the structure of individual influence structures among Supreme Court justices and the ideological structure of the key issues that split the court. A Tool Kit for Practice Theory. Poetics 27 (2000):
32 D. Duality Analysis - Examples of Applying Duality Analysis to Culture Bernard Harcourt examines the duality of youth Gun practices and Gun ideologies. Measured Interpretation: Introducing the Method of Correspondence Analysis to Legal Studies. University of Illinois Law Review vol (2003):
33 D. Duality Analysis - Examples of Applying Duality Analysis to Culture John Martin examines the duality of animal species and occupational types. What do animals do all day? The division of labor, class bodies, and totemic thinking in the popular imagination. Poetics vol. 27 (2000):
34 G. Duality Analysis - Examples of Applying Duality Analysis to Culture John Mohr & Francesca Guerra-Pearson The Duality of Niche and Form: The Differentiation of Institutional Space in New York City, Pp in Categories in Markets: Origins and Evolution, (Research in the Sociology of Organizations, Vol. 31) 34
35 D. Duality Analysis - Examples of Applying Duality Analysis to Culture Mohr, John W. and Helene K. Lee From Affirmative Action to Outreach: Discourse Shifts at the University of California. Poetics: Journal of Empirical Research on Literature, the Media, and the Arts. Special Issue on Culture and Cognition edited by Karen Cerulo Vol. 28/1:47-71 Figure 3. Race Discourse Structure of Boundary Programs Intellectual Skills Poverty Exceptional Ability 35
36 D. Duality Analysis - Examples of Applying Duality Analysis to Culture Happiness as the Duality of Ritual & Belief with Josep Rodriguez at U Barcelona. 36
37 IV. Text Mining Tools and the Formal Analysis of Culture. 37
38 A. New Developments in Digital Humanities More recent work: Franco Moretti Network Theory, Plot Analysis. New Left Review 68: Use networks tools to map plot structure in Shakespeare vs. Traditional Chinese Novels. 38
39 A. New Developments in Digital Humanities 39
40 B. LDA Topic Models. * Taken from David Blei, Princeton: 40
41 Poetics (Special Issue) Forthcoming December 2013 Topic Models and the Cultural Sciences Edited by John Mohr and Petko Bogdanov Topic models: What they are and why they matter. John Mohr (Soc. UCSB) and Petko Bogdanov (CS UCSB) Exploiting Affinities between Topic Modeling and the Sociological Perspective on Culture: Application to Newspaper Coverage of Government Arts Funding in the U.S. Paul DiMaggio (Sociology, Princeton University), Manish Nag (Sociology, Princeton University), and David Blei (Computer Science, Princeton University). Differentiating Language-Usage Through Topic Models Daniel A. McFarland (Education, Stanford), Daniel Ramage, Jason Chuang, Jeff Heer, Christopher D. Manning (Computer Science, Stanford) and Daniel Jurafsky (Linguistics, Stanford Rebellion, crime and violence in Qing China, : a topic modeling approach to the great unread. Ian Miller (History, Harvard University) 41
42 Elevated Threat-Levels and Decreased Expectations: How Democracy Handles Terrorist Threats Tabitha Bonilla and Justin Grimmer (Political Science, Stanford). Graphing the Grammar of Motives in U.S. National Security Strategies: Cultural Interpretation, Automated Text Analysis and the Drama of Global Politics John W. Mohr (Sociology, UCSB), Robin Wagner-Pacifici (Sociology, The New School), Ron Breiger (Sociology, U of Arizona), Petko Bogdanov (Computer Science, UCSB). Defining Population Problems: Using Topic Models for Cross-National Comparison of Disciplinary Development. Emily Marshall (Department of Sociology, University of Michigan) Trawling in the Sea of the Great Unread: Sub-Corpus Topic Modeling and Humanities Research. Peter Leonard (University of Chicago) and Tim Tangherlini (Scandinavian Studies, UCLA) Significant Themes: Topic Modeling the 19th-Century Novel Matthew L. Jockers (Department of English, University of Nebraska-Lincoln) and David Mimno (Department of Information Science, Cornell University) 42
43 43
44 V. Recent Work using Text Mining Tools to the Pursue the Formal Analysis of Culture. 44
45 Using LDA Topic Models: New Project looks at evolution of discourse logics in U.S. National Security Strategy Statements ( ) Ron Breiger (UA), Robin Wagner-Pacifici (New School) and Petko Bogdanov (CS, UCSB). Is there a deep structure? An implicit moral ordering? 45
46 1I. What are the NSS docs? Origins: the Goldwater- Nichols legislation 1986 intended to address interservice rivalry & chain of command (but also demanded a public accountability from Exec Branch by asking for annual review in the NSS). Probably most famous was the 2002 NSS in which Bush administration laid out principles of the right of a preemptive attack (justifying the invasion of Iraq). 46
47 Graphing the Grammar of Motives in U.S. National Security Strategies: Cultural Interpretation, Automated Text Analysis and the Drama of Global Politics (forthcoming, Poetics, 2013) John W. Mohr (Sociology, UCSB), Robin Wagner-Pacifici (Sociology, The New School), Ron Breiger (Sociology, U of Arizona), Petko Bogdanov (Computer Science, UCSB). Draws on work of Kenneth Burke ( ) A literary theorist developed a Dramatistic Theory The best model that we have for studying the meaningfulness of human discourse is to look to the models of that discourse that humans have themselves made, which is to say we should examine the literary, the poetic, and the dramatic as exemplars for understanding human meanings. 47
48 Kenneth Burke We shall use five terms as generating principle of our investigation. They are: Act, Scene, Agent, Agency, Purpose. In a rounded statement about motives, you must have some word that names the act (names what took place, in thought or deed), and another that names the scene (the background of the act, the situation in which it occurred); also, you must indicate what person or kind of person (agent) performed the act, what means or instruments he used (agency), and the purpose. Men may violently disagree about the purposes behind a given act, or about the character of the person who did it, or how he did it, or in what kind of situation he acted; or they may even insist upon totally different words to name the act itself. But be that as it may, any complete statement about motives will offer some kind of answers to these five questions: what was done (act), when or where it was done (scene), who did it (agent), how he did it (agency), and why (purpose) (1945, p. xv). 48
49 Current work combining three types of text-mining tools: 1. Use (enhanced) Natural Language Processing tools to find all Agents. 2. Use syntactic parser to tag parts of speech (at the sentence level) to find Acts. 3. Use topic models to sift the text for more coherent discussion frames to find Scenes 49
50 NER finds Agents 50
51 State based Agents 51
52 Regions as Agents 52
53 People & Orgs as Agents 53
54 1990 NSS George H. W. Bush (Concept-Verb or Verb-Concept 3+) 54
55 1990 NSS George H. W. Bush (Concept- Verb-Concept 3+) 55
56 1991 NSS George H. W. Bush (Concept- Verb-Concept 3+) 56
57 1995 NSS William Clinton (Concept-Verb-Concept 3+) 57
58 1996 NSS William Clinton (Concept-Verb-Concept 3+) 58
59 2002 NSS George W. Bush (Concept-Verb-Concept 3+) 59
60 2010 NSS Barack Obama (Concept-Verb-Concept 3+) 60
61 15 Level Topic Model of NSS Corpus Topic Distribution Across Years 61
62 1990 NSS George H. W. Bush (Concept- Verb-Concept) Topic = 0 (Terrorism) 62
63 1991 NSS George H. W. Bush (Concept- Verb-Concept) Topic = 0 (Terrorism) 63
64 2002 NSS G.W. Bush: All Agent x verb x Agent ties in paragraphs with topic of Terrorism. 64
65 2002 NSS George W. Bush (Concept-Verb; Verb-Concept) Topic = 5 (Energy) 65
66 2002 NSS George H. W. Bush (Concept-Verb-Concept) Topic = 7 (Conflict) 66
67 2010 NSS Barack Obama (Concept-Verb-Concept) Topic = 7 (Conflict) 67
68 Conclusions: 1. Big Data is (potentially) very good for social science. 2. Still need work in how to use formal models to analyze ideas and culture. 3. Exs. from sociology of culture (relationality/duality). 4. As sociology of culture moves forward to meet the rise of Big Data, so too duality of cultural forms are critical. 68
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