Research Centre for Japanese Language and Linguistics University of Oxford www.orinst.ox.ac.uk/research/jap-ling/ Maria Telegina maria.telegina@orinst.ox.ac.uk EALS 17 January 2017 !  !  !  !  !  Motivation Free word association experiment Network Analysis Time and Space in Japanese culture in theoretical works Conclusions 2 !  Part of my doctoral thesis Time and Space Concepts in Japanese Language World View   escription and analysis of models of d temporal and spatial concepts specific to the Japanese language and to modern Japanese culture Data->Network->Network Statistics ->Interpretation (Factors affecting associations: Age?) 3 !  Objectives:  Key words   Communities Structure  Theory vs. Experimental data 4 !  Stimuli Selection Criteria   requencies according to Frequency Dictionary of F Japanese (2013)  Semantic relations within the stimuli set:   Synonyms are chosen in accordance with WordNet ver. 1.1   Hyponyms, hypernyms, and antonyms are selected in accordance with the Japanese Word Association Database ver. 1 (2004) and the Associative Concept Dictionary (2004, 2005) 5 !  Stimuli set 6 !  Gap/room Stimuli set Timing Room/space Place(basho) Time/interval/space Time(jikan) m Space(kuukan) Distance Spread km Length Time/period/season Era/generation 2015 Age 63 Free/not busy Long time Morning 11 1125 House/home Date/day Night NHKE 48 LDK Inside Outside Day/sun 18 622 Suburb One's house/one's home 7 15 Living room(ima) Holiday/day off Daytime 1111 Apartament(manshon) Holiday/rest Living room(ribingu) 19 1980 In the city Room Apartment(apaato) Time(toki) Summer Time/era Space(supeesu) km good Season Gap/opening Distance/period 1 Moment/instant Place/occasion(ba) One's home Inner part/depth Behind/back 49 12 9 Past/old times Autumn Past Future Front/before 7 !  Participants(1)  85 Japanese native speaking participants  Two groups:   roup 1(average age G 21)   roup 2(average age G 62) 8 !  Participants(2)   ost of the M participants from the Kanto area 9 !  Participants(3) 10 !  Definitions of Network   From a formal point of view, a network (or a graph) is a set of vertices connected via edges. S.N. Dorogovtsev and J.F.F. Mendes(2003)   A network (or a graph) is a set of nodes connected by links. S.N. Dorogovtsev (2010)   Graphs are assigned by giving a set of the vertices and a set of connections between them. Guido Caldarelli (2007) 11 !  Examples   Citation and collaboration networks   Acquaintances networks   Associative/Semantic networks   On-line behavior/communication patterns 12 !  What can we study about a system using network?   Nature of individual components   Connections or interactions   Pattern of connections 13 Measure Group 1 Group 2 Both groups N of nodes 919 849 1423 N of Edges 1337 1234 2234 Density 0.002 0.002 0.001 Average path 5.302 4.502 4.326 Network diameter 13 10 10 Av. In-degree 1.455 1.453 1.569 Av.weighted in-degree 2.378 2.15 2.818 Av.clustering coefficient 0.066 0.055 0.076 14 !  Measure (1): In-degree  In-degree centrality - a number of incoming connections of a node  Shows words strongly connected with the whole network -> key-words ID a b c d e Indegree 0 1 2 1 1 15 Liking) Stimuli Translation Home; house 奥 Total N of responses 3 Holiday; rest 2 Spare time 2 Inner part 1 One's home 1 Outside 1 Holiday; day off 1 In the city 1 Moment; instant 1 Long period of time 1 14 16 Emotional Evaluation (positive) Associative Response Translation In-Degree Liking 10 Relaxation; comfort 9 Important; necessary/ beloved; precious 9 To calm down 7 Enjoyable; fun 7 Important; valuable 6 Peace of mind 5 Convenient; handy 4 Good 3 Joy; delight; 3 Dear; missed 3 Happy; glad; pleasant 3 Pretty; lovely; beautiful 2 Emotional Evaluation (negative) Associative Translation Response InDegree Uneasiness; insecurity 5 Scary; frightening; 4 Danger 3 Accident; incident; trouble 3 Dangerous; risky 2 Dislike; hate 2 17 In-degree Group1 Group2 Both groups Home; house Time Time Time Space Narrow Narrow Narrow Space Spacious; wide Ease; relaxation Space Important; necessary Room Room Family Spacious; wide Gap; break Spacious; wide Like Like Freedom Ease; relaxation Work Important; necessary Children Gap; break Now History Home; house 18 Human relations/society Associative Response Translation In-Degree Family 7 Man; person 6 Child; children 6 Myself 5 Human relations 5 Living; life 5 Action; conduct; behavior 3 Conversation 3 Communication 2 Friend 2 Company; fellow 2 (human) Life 4 19 !  Measure (2): Weighted In-degree   Weighted In-degree centrality – is a sum of weights of incoming connections   Shows words strongly connected with words from the stimuli set -> semantically/ associatively related words ID a b c d e Degree 0 1 12 3 2 20 夢 (Dream) Stimuli Translation N of responses One's home; one's house 9 Future 5 Total 14 Four seasons) Stimuli Translation N of responses 季節 Season 14 Time; period; season 2 Total 16 21 Weighted in-degree Group1 Group2 Both groups Home; house Space Space Time Family Time Space Time Home; house Sun Bright/light Sun Hot Sun Family Spacious; wide Outside Narrow Narrow Inside Spacious; wide Gap; opening Narrow Bright; light Long Past Past Past Relaxation Gap; opening 22 Partial Synonym Stimuli (Family) Translation N of responses One's house; one's home 10 Home; house 9 Living room 8 One's house; one's home 6 Living room 5 Inside 2 Space 1 41 Antonym Stimuli 奥 (Outside) Translation N of responses Inside 18 Suburb; outskirts 4 Interior; inner part 1 23 23 !  Important works Kato, S. 2007. Time and Space in Japanese Culture http://fuji-san.txt-nifty.com Inoue, S. et al., 1996. Sociology of Time and Space https://www.iwanami.co.jp 24 !  Three concepts of time: !  Historical Time – linear; no beginning, no end !  Day-to-day Time – cyclical; no beginning, no end !  Universal Lifetime – linear; irreversible; with beginning and end Kato (2007), Mita (1996) 25 !  Three concepts of space: !  Open - people and information can easily get in and get out !  Half-open – people and information can get in and get out, though outward flow is less welcome !  Closed – very strict differentiation between “inside” and “outside”; no strangers can get in. Kato (2007) 26 !  Methodology   Order Statistics Local Optimization Method(OSLOM) (Lancichinetti, A., Radicchi, F., Ramasco, J.J., Fortunato S. , 2011) !  looks for significant clusters !  analyzes the resulting set of clusters, trying to detect their internal structure !  detects the hierarchical structure of the clusters 27 !  High hierarchical level   Two big communities – Time and Space   Small community – In front; behind 28 !  Lower hierarchical level   11 communities: !  Abstract Time !  Natural processes time !  Seasonal time !  Calendar Time !  Free time !  Abstract Space !  City/countryside !  Outside/inside (home) !  Room (life space) !  In front/behind !  Depth/unknown 29 !  Three concepts of time: !  Historical Time – linear; no beginning, no end ! Day-to-day Time – cyclical; no beginning, no end !  Universal Lifetime – linear; irreversible; with beginning and end Kato (2007), Mita (1996) 30 !  Three concepts of space: !  Open - people and information can easily get in and get out !  Half-open – people and information can get in and get out, though outward flow is less welcome !  Closed – very strict differentiation between “inside” and “outside”; no strangers can get in. Kato (2007) 31 !  Communities Overlaps: !  Natural processes time & Seasonal time (45 nodes) !  Calendar time & Abstract time (12 nodes) !  Depth/unknown & Abstract time (10 nodes) !  Natural processes time & Calendar Time (7) 32 !  Individual node overlaps 未来 (Future) (Relaxed/ spacious) Communities In front; behind Depth; unknown Communities Natural processes time Free time Abstract Time City/countryside (Long) Communities Abstract Time Abstract Space 33 !  !  !  Network Analysis -> processes within network & its structure & important elements Single word level->semantic features based on connectivity Network level-> understanding of structure and hierarchy of the concepts E.g. Data driven concepts of time and space not shown in the theoretical works 34 !  !  !  More data! Character of semantic relations by native speakers Comparison with corpora based network 35 Research Centre for Japanese Language and Linguistics University of Oxford www.orinst.ox.ac.uk/research/jap-ling/ Maria Telegina maria.telegina@orinst.ox.ac.uk