SLANG Introduction1 - uni-tuebingen.deroland/SLANG13/Latex/intro01.pdf · Final project...
Transcript of SLANG Introduction1 - uni-tuebingen.deroland/SLANG13/Latex/intro01.pdf · Final project...
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SLANGIntroduction 1
Roland MuhlenberndSeminar fur Sprachwissenschaft
University of Tubingen
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Introduction
I Roland Muhlenbernd
Email: [email protected]
Π Room 1.24 (Wilhelmstr. 19)
w3 http://www.sfs.uni-tuebingen.de/˜roland/SLANG13
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Introduction: Course Info
I Time: Wednesday 14-16
I Place: VG 0.02
I Tasks: regularly short homeworks, presentation + review
I Assessment table:
Task Detail Assessment
Homework 10× homeworks 50% = 10× 5%Final project presentation + review 50% = 30% + 20%
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Introduction: SLANG & PENG Topics
’PENG’: Project group Evolutionary Network Games (each WS)
I Lecturer: Roland Muhlenbernd
I Place: Room VG 2.26
SLANG PENG
Sociology/Sociolinguistics
Network theory
Languageevolution
Game theory/Signaling games
Language use
Language change
Network games& Simulations
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Introduction: SLANG & PENG Skills
’PENG’: Project group Evolutionary Network Games (each WS)
I Lecturer: Roland Muhlenbernd
I Place: Room VG 2.26
SLANG PENG
Discussion/Reviewing
Lecture/Talk
Project Work/Programing
Brainstorming/Designing/
Creating
Presenting
Team Work
LiteratureResearch
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Introduction: Linguistics & Sociolinguistics
What is Sociolinguistics?Labov: Division in the Foundations of Linguistics
Classical Linguistics Sociolinguistics
Phil. Opposition Idealism MaterialismExemplary - Generative Grammar - Phonetics
Fields - Generalized PSG - Historical Linguistics- Lexical-Funct. Grammar - Dialectology
View Language is property Language is propertyof an individual of the speech community
Competence get underlying C; C can only be understoodPerformance P is outside ling. proper through the study of PCommunity ...is inconsistent mixture structured heterogeneity
of consistent individuals is fundamental featureProduction neutral to both, but if prod. is methodologically
Perception precedence: perception & epistemologically priorMathematic qualitative, algebraic quantitative, probabilistic
Models based on introspection observation/experiments
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Introduction: From Experiments/Evidence to Theory
Classical Linguistics Sociolinguistics
Idealism MaterialismExemplary - Generative Grammar - Phonetics
Fields - Generalized PSG - Historical Linguistics- Lexical-Funct. Grammar - Dialectology
View Language is property Language is propertyof an individual of the speech community
Competence get underlying C; C can only be understoodPerformance P is outside ling. proper through the study of PCommunity ...is inconsistent mixture structured heterogeneity
of consistent individuals is fundamental featureProduction neutral to both, but if prod. is methodologicallyPerception precedence: perception & epistemologically priorMathematic qualitative, algebraic quantitative, probabilistic
Models based on introspection observation/experiments
”How far can we go with unsupported qualitative analysis based onintrospection, before the proposal must be confirmed byquantitative studies based on observation and experiment?”(Labov, 1987)
Some Observations on the Foundation of Linguistics (Labov, 1987)
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Introduction: From Theory to Models/Experiments
Why should we use networks for social, linguistic or sociolinguisticphenomena?
I Synchronic analyses
I Depicting/Modeling the structure of a community (. network)I Analyzing the properties of network members (. agents)I Analyzing the properties of (parts of) networks
Why should we use simulations in our research?
I Diachronic analyses
I Depicting the evolution of a network (. simulation)I Analyzing mentioned properties extended by dimension of time
Why should we apply Game Theory?
I Modeling of behavior
I Communicative behavior/language use and it’s impactsdepends on at least two participants (. game)
I Language is often used in a rational way (. rationality)
Signaling & Simulations in Sociolinguistics (Muhlenbernd & Quinley, 2013)
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Introduction: Sessions
1. Linguistic Phenomena in SocietiesI Dialects, Variation, Language DeathI Register, Politeness
2. Sociolinguistic Forces: From Observations to TheoryI Weak and Strong TiesI Transmission & Diffusion
3. Simulations on Social NetworksI Network Structure & Network PropertiesI Social Impact Theory, Naming Game
4. Game Theory and LinguisticsI Prisoner’s Dilemma, Stag Hunt, CooperationI Signaling Games, Language Use as Rational Behavior
5. Games on Networks: Simulating Linguistic Phenomena
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Session I: Language Variation & Language Change
1. Language Variation: How does language differ over space?I IdiolectsI SociolectsI DialectsI Languages
2. Language Change: How does language differ over time?I Language EvolutionI Language ContactI Language Death
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Session II: Sociolinguistc Forces: Observations → Theory
What causes Language Variation?
I Geography
I Social Class, Gender, Education
I Social Network/ Interaction Structure
I Language Contact
I Prestige
What removes Language Variation?
I Weak Ties
I Language Death
I Media
I Power
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Session II: Sociolinguistc Forces: Observations → Theory
What should we keep in mind when modeling variation?
I Variation in Connectivity: Weak vs. Strong Ties
I Variation in Position: Power, Prestige
I Variation over Space: Dialects, Sociolects
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Session II: Sociolinguistc Forces: Weak vs. Strong Ties
Social network and social class (Milroy & Milroy)
I Close-knit networks function as conservative force, resistingpressure for change
I Close-knit networks maintain and enforce local convention
I Innovations between groups are generally transmitted bymeans of weak network ties
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Session II: Sociolinguistc Forces: Power and Prestige
How do power and prestige affect language variation on themacro-level?
I Dialectism (Labov)
I Jargon vs. Slang
I Multi-lingualism; e.g. India
Micro-level?
I (Im)Politeness (Morand, Labov, Parkin)
I Register, Social Mobility, and Idiolect
I Information Transmission vs. Relationship Negotiation(Pinker)
I Code-Switching
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Session III: Simulations on Social Networks
1. What is the Scientific Method?I ResearchI TheorizeI TestI Evaluate
2. What does that mean for our course?I Computational Models Simulate Linguistic ProcessesI Linguistic Data Informs Theories/ Models
TheoryField Work,
Research
Comp. Model,
Simulation
structure, behaviour
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Session III: Simulations on Social Networks
Pros and Cons: Simulation compared with field work
I + Less expensive, less effort
I + More independent of external influences
I + Faster than real time
I + Simulate the past/future
I +/- (Much) more abstract
I - Less realistic
I - Less innovative in revealing new phenomena
I - Depends on Field Work data for alignment with real worldphenomena
Good combination: Validity of field work + power of simulation
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Session III: Network Representations
Network representation as Graph (set of nodes & adjacency matrix)
I Graph G = (N, g)
I N = {1, 2, 3, 4}
I g =
0 1 0 10 0 0 11 1 0 00 0 1 0
1 2
3
4
I Graph G = (N, g)
I N = {1, 2, 3, 4}
I g =
0 1 1 01 0 1 01 1 0 10 0 1 0
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Session III: Network Representations
Network representation as Graph (set of nodes & set of edges)
I Graph G = (N,E )
I N = {1, 2, 3, 4}I E = {〈1, 2〉, 〈1, 4〉, 〈2, 4〉,
〈3, 1〉, 〈3, 2〉, 〈4, 3〉}
1 2
3
4
I Graph G = (N,E )
I N = {1, 2, 3, 4}I E = {{1, 2}, {1, 3},
{2, 3}, {3, 4}}
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Session III: Subgraphs, Cliques & Components
I A subgraph/ subnetwork is asubset of the original graph’sconnections.
I A clique is a maximallyconnected subgraph. Howmany edges will a clique have?
I A component is a connectedsubgraph that is notconnected to other subgraphsof the network.
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Session III: Classical network structures
Star network
9
12
3
45
6
7
8
Ring network
12
3
45
6
7
8
Tree network
1
2 3
4 5 6 7
Complete network
1 2
3 4
Easy to analyze, but not realistic to describe Human networks!!!
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Session III: Small-World Networks
The ”Six degrees of separation” (F. Karinthy, 1929)
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Session III: Small-World Networks
The Small world experiment is a collection of several experimentsexamining the average path length for social networks of people inthe United States.
Basic procedure: Postcard questioning (S. Milgram, 1967)
I Starting point S : Omaha, Nebraska and Wichita, Kansas
I End point E : Boston, Massachusetts
I Ask a random s ∈ S : Do you know (random) e ∈ E ?
I If not, do you know x who could know e ∈ E ?
I Ask x : Do you know e ∈ E ?
I etcetera
Result: Average path length of around 5.5
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Session III: Small-World Networks
I The ”Six degrees of Kevin Bacon”Example: Elvis Presley played togetherwith Edward Asner in ”Change of habit”(1969). Edward Asner played with KevinBacon in ”JFK” (1991). Elvis Presley hasBacon-Number 2.Result: As of December 2010, the highestfinite Bacon number reported by theOracle of Bacon is 9.
I ”Erdos number”...describes the ”collaborative distance”between a person and mathematicianPaul Erdos, as measured by authorship ofmathematical papers.Result: Erdos had 511 direct collaborators(1). In 2007 there were 8,162 people withErdos number 2.
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Session III: Small-World Networks
I Large networkI High Clustering CoefficientI Small Average Path Length
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Session IV: Game Theory & Linguistics
What is Game Theory?
I Game theory (GT) is designed to model situations in whichagents can make decisions and their outcome depends not onlyon their own, but also on the decisions, other agents make
I GT is a tool to model interdependent behavior. E.g. RationalBehavior, Decisions, Strategy.
I Unified Theory for Social Sciences
I Applications in Economics, Biology, Sociology, Linguistics
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Session IV: Game Theory & Linguistics
Questions of Interest
I What are some mechanisms that can explain Cooperation andAltruism?
I Why do we see conspicuous consumption and showy behavior?
I How much cognitive capacity do we need for optimal behaviorto emerge?
I How do our beliefs (about others, our situation, etc.) affectour behavior?
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Session IV: Game Theory & Linguistics
Example:There is a boxing fight between Rocky and Henry. The price forthe winner is 6 million $. The winning chance for both is 1:1. Ifone boxer gets an advantage by taking a special legal drug beforethe fight, his winning chance is 5:1, but the drug costs 1 million $.Before the fight both boxers have to decide, if they take the drugor not. How do you think will they behave?
HenryND D
Rocky ND 3;3 1;4D 4;1 2;2
Again: How do you think will they behave?
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Session IV: Prisoners’ Dilemma
I The boxing example is an instance of the Prisoners’ Dilemma
I C stands for “cooperate” and D for “defect”
C D
C 3;3 0;5D 5;0 1;1
Tabelle : Prisoner’s Dilemma
I What will the Players do?
I Are there ways that they might change their strategy?
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Homework 1
1. Read the article ’Some Observations on the Foundation ofLinguistics’ (Labov, 1987) and answer the following question:
I What are Labov’s arguments for and against the materialistand idealist position/view of linguistics?
2. Read the article ’Signaling and Simulation in Sociolinguistics’(Muhlenbernd & Quinley, 2013) and answer the following question:
I Which studies are discussed in Section 3 and Section 5? Give adescription of 2-3 sentences for each of them.
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Homework 1
3. Take a look at the webpage and choose a subject you want togive your presentation about and an appropriate date (first come /first serve). Preliminary schedule:
1. Phenomena/Theories in Sociolinguistics (May 8. , 15. , 22. , 29.)
2. Network Theory & Simulations (June 5. , 12.)
3. Game Theory & Linguistics (June 19. , 26. , July 3.)
4. Games on Networks (July 10. , 17.)