Crawling forward: A multidimensional scaling analysis of path and manner

1. Crawling forward:A multidimensional scaling analysis of path and manner Michele I. Feist and Steven J. Clancy University of Louisiana at Lafayette and University of Chicago This presentation is based on work Feist and Clancy did in Odense Denmark, July 2008 with the following EMCL-4 Students: Austin N. Bennett, Hanne M. Eckhoff, Sayane Gouroubéra, Sun Hee Park, Karen Sullivan, Alastair Wilson

2. Introduction • Human motion events • Path • The man entered the room. • Manner • The man walked into the room.

3. Introduction • Path languages • Romance (e.g. French, Spanish) • Semitic (e.g. Hebrew, Arabic) • Japanese, Basque, Turkish, Mayan, Inuit, Korean • Manner languages • Germanic (e.g. English, Danish, German) • Slavic (e.g. Russian, Polish) • Finno-Ugric (e.g. Hungarian) • Thai, Mandarin Chinese Slobin (2004); Talmy (1985, 2000)

4. Can we use computational methods such as MDS to support and extend these observations?

5. Methodology • Experimental methodology • We constructed a set of stimuli able to elicit both construals of motion • 25 videos exhaustively permuted 5 paths and 5 manners Aimless, circle, forward, through a door, up some stairs Crawl, jump, run, twirl, walk • We pseudo-randomised the ordering of the videos • We asked for a simple description of what happened in the participants’ native languages • We also asked for the main verb to be identified

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7. Methodology • The methodology of our analysis • We used MDS to gauge the relative importance of path and manner in our sample by constructing a conceptual space • We also constructed subsets to show the different language types

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12. Results and analysis • Different dimensions • We used the Optimal Classification MDS algorithm to create similarity spaces to account for our data • We ran 1, 2 and 3 dimensional analyses and found that the 2 dimensional analysis provided the most insights and the most accuracy

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20. Results and analysis • Advantages of MDS • Different language types can be combined in one space • Axes need not reflect semantic factors, as in semantic maps • An elegant summary can be presented with fewer dimensions than a semantic map • An economical way to construct conceptual spaces

21. MDS as support for typology • Evidence for coherent manner clusters • In overall data set • In manner languages • Evidence for coherent path clusters • In path languages • Results are consistent with Slobin (2004) French and Spanish are “pathy” languages English, German, Russian and Thai are manner languages

22. MDS to extend typology • Path salience [STAIRS, DOOR] > CIRCLE > [FORWARD, AIMLESS] The role of boundaries and objects • Manner salience CRAWL > RUN > JUMP > [TWIRL, WALK] Speed and position, and the unmarked nature of walking

23. Conclusions • Summary • MDS confirmed the relevance of Manner and path in the conceptual space for motion events • MDS allows for analysis beyond binary language types • MDS allows us to see different construals of space in one visual representation

24. Conclusions • Limitations • Lack of detailed glossing and speaker overriding • Language bias – Indo-European and Germanic • Small sample and English-speaking environment More evidence for manner than path in our pilot data • Further research • Combating bias • More speakers per language • More balanced language sample • Is aimless a manner? • How does boundary interact with path?

25. Crawling forward:A multidimensional scaling analysis of path and manner Michele I. Feist and Steven J. Clancy University of Louisiana at Lafayette and University of Chicago