1887
Volume 17, Issue 1
  • ISSN 1871-1340
  • E-ISSN: 1871-1375

Abstract

Abstract

Previous evidence has implicated personal relevance as a predictive factor in lexical access. Westbury (2014) showed that personally relevant words were rated as having a higher subjective familiarity than words that were not personally relevant, suggesting that personally relevant words are processed more fluently than less personally relevant words. Here we extend this work by defining a measure of personal relevance that does not rely on human judgments but is rather derived from first-order co-occurrence of words with the first-person singular personal pronoun, . We show that words estimated as most personally relevant are recognized more quickly, named faster, judged as more familiar, and used by infants earlier than words that are less personally relevant. Self-relevance is also a strong predictor of several measures that are usually measured only by human judgments or their computational estimates, such as subjective familiarity, age of acquisition, imageability, concreteness, and body-object interaction. We have made all self-relevance estimates (as well as the raw data and code from our experiments) available at https://osf.io/gdb6h/.

Available under the CC BY-NC 4.0 license.
Loading

Article metrics loading...

/content/journals/10.1075/ml.20031.wes
2022-03-18
2022-05-21
Loading full text...

Full text loading...

/deliver/fulltext/ml.20031.wes.html?itemId=/content/journals/10.1075/ml.20031.wes&mimeType=html&fmt=ahah

References

  1. Akaike, H.
    (1973) Information theory and an extension of the maximum likelihood principle. InB. N. Petrov & F. Caski. (Eds.), Proceedings of the Second International Symposium on Information Theory (pp.267–281). Budapest: Akademiai Kiado.
    [Google Scholar]
  2. (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716–723. 10.1109/TAC.1974.1100705
    https://doi.org/10.1109/TAC.1974.1100705 [Google Scholar]
  3. Alexopoulos, T., Muller, D., Ric, F., & Marendaz, C.
    (2012) I, me, mine: Automatic attentional capture by self-related stimuli. European Journal of Social Psychology, 42, 770–779. 10.1002/ejsp.1882
    https://doi.org/10.1002/ejsp.1882 [Google Scholar]
  4. Baayen, R. H.
    (2010) Demythologizing the word frequency effect: A discriminative learning perspective. The Mental Lexicon, 5(3), 436–461. 10.1075/ml.5.3.10baa
    https://doi.org/10.1075/ml.5.3.10baa [Google Scholar]
  5. Baayen, R. H., Feldman, L. B., & Schreuder, R.
    (2006) Morphological influences on the recognition of monosyllabic monomorphemic words. Journal of Memory and Language, 55(2), 290–313. 10.1016/j.jml.2006.03.008
    https://doi.org/10.1016/j.jml.2006.03.008 [Google Scholar]
  6. Balota, D. A., Pilotti, M., & Cortese, M. J.
    (2001) Subjective frequency estimates for 2,938 monosyllabic words. Memory & Cognition, 29(4), 639–647. 10.3758/BF03200465
    https://doi.org/10.3758/BF03200465 [Google Scholar]
  7. Balota, D. A., Yap, M. J., Hutchison, K. A., Cortese, M. J., Kessler, B., Loftis, B., Neely, J. H., Nelson, D. L., Simpson, G. B. & Treiman, R.
    (2007) The English Lexicon Project. Behavior Research Methods, 39(3), 445–459. 10.3758/BF03193014
    https://doi.org/10.3758/BF03193014 [Google Scholar]
  8. Bird, H., Franklin, S., and Howard, D.
    (2001) Age of acquisition and imageability ratings for a large set of words, including verbs and function words. Behavior Research Methods, Instruments, & Computers, 33, 73–79. 10.3758/BF03195349
    https://doi.org/10.3758/BF03195349 [Google Scholar]
  9. Bonin, P., Peereman, R., Malardier, N., Méot, A., & Chalard, M.
    (2003) A new set of 299 pictures for psycholinguistic studies: French norms for name agreement, image agreement, conceptual familiarity, visual complexity, image variability, age of acquisition, and naming latencies. Behavior Research Methods, Instruments, & Computers, 35(1), 158–167. 10.3758/BF03195507
    https://doi.org/10.3758/BF03195507 [Google Scholar]
  10. Brown, G. D., & Watson, F. L.
    (1987) First in, first out: Word learning age and spoken word frequency as predictors of word familiarity and word naming latency. Memory & cognition, 15(3), 208–216. 10.3758/BF03197718
    https://doi.org/10.3758/BF03197718 [Google Scholar]
  11. Cortese, M. J., & Khanna, M. M.
    (2008) Age of acquisition ratings for 3,000 monosyllabic words. Behavior Research Methods, 40(3), 791–794. 10.3758/BRM.40.3.791
    https://doi.org/10.3758/BRM.40.3.791 [Google Scholar]
  12. Davies, M.
    (2010) The Corpus of Contemporary American English as the first reliable monitor corpus of English. Literary and Linguistic computing, 25(4), 447–464. 10.1093/llc/fqq018
    https://doi.org/10.1093/llc/fqq018 [Google Scholar]
  13. Ferrand, L., Bonin, P., Méot, A., Augustinova, M., New, B., Pallier, C., & Brysbaert, M.
    (2008) Age-of-acquisition and subjective frequency estimates for all generally known monosyllabic French words and their relation with other psycholinguistic variables. Behavior Research Methods, 40(4), 1049–1054. 10.3758/BRM.40.4.1049
    https://doi.org/10.3758/BRM.40.4.1049 [Google Scholar]
  14. Ferrand, L., Grainger, J., & New, B.
    (2003) Normes d’âge d’acquisition pour 400 mots monosyllabiques [Age-of-acquisition norms for 400 monosyllabic French words]. L’Année Psychologique, 103, 445–467. 10.3406/psy.2003.29645
    https://doi.org/10.3406/psy.2003.29645 [Google Scholar]
  15. Flieller, A., & Tournois, J.
    (1994) Imagery value, subjective and objective frequency, date of entry into the language, and degree of polysemy in a sample of 998 French words. International Journal of Psychology, 29(4), 471–509. 10.1080/00207599408246553
    https://doi.org/10.1080/00207599408246553 [Google Scholar]
  16. Frings, C., & Wentura, D.
    (2014) Self-priorization processes in action and perception. Journal of Experimental Psychology: Human Perception and Performance, 40(5), 1737.
    [Google Scholar]
  17. Gernsbacher, M.A.
    (1984) Resolving 20 years of inconsistent interactions between lexical familiarity and orthography, concreteness, and polysemy. Journal of Experimental Psychology: General, 113(2), 256. 10.1037/0096‑3445.113.2.256
    https://doi.org/10.1037/0096-3445.113.2.256 [Google Scholar]
  18. Ghyselinck, M., De Moor, W., & Brysbaert, M.
    (2000) Age-of-acquisition ratings for 2816 Dutch four-and five-letter nouns. Psychologica Belgica, 40(2), 77–98. 10.5334/pb.958
    https://doi.org/10.5334/pb.958 [Google Scholar]
  19. Gilhooly, K.J., and Logie, R. H.
    (1980) Age-of-acquisition, imagery, concreteness, familiarity, and ambiguity measures for 1,944 words. Behavior Research, Methods Instruments, and Computers, 12, 395–427. 10.3758/BF03201693
    https://doi.org/10.3758/BF03201693 [Google Scholar]
  20. Golubickis, M., Falben, J. K., Cunningham, W. A., & Macrae, C. N.
    (2018) Exploring the self-ownership effect: Separating stimulus and response biases. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(2), 295.
    [Google Scholar]
  21. Hart, B.
    (1991) Input frequency and children’s first words. First Language, 11(32), 289–300. 10.1177/014272379101103205
    https://doi.org/10.1177/014272379101103205 [Google Scholar]
  22. Hempel, C. G., & Oppenheim, P.
    (1948) Studies in the Logic of Explanation. Philosophy of Science, 15(2), 135–175. 10.1086/286983
    https://doi.org/10.1086/286983 [Google Scholar]
  23. Hollis, G.
    (2020) Delineating linguistic contexts, and the validity of context diversity as a measure of a word’s contextual variability. Journal of Memory and Language, 114, 104–146. 10.1016/j.jml.2020.104146
    https://doi.org/10.1016/j.jml.2020.104146 [Google Scholar]
  24. Hollis, G., & Westbury, C.
    (2016) The principals of meaning: Extracting semantic dimensions from co-occurrence models of semantics. Psychonomic Bulletin & Review, 23(6), 1744–1756. 10.3758/s13423‑016‑1053‑2
    https://doi.org/10.3758/s13423-016-1053-2 [Google Scholar]
  25. Hollis, G., Westbury, C., & Lefsrud, L.
    (2017) Extrapolating human judgments from skip-gram vector representations of word meaning. The Quarterly Journal of Experimental Psychology, 70(8), 1603–1619. 10.1080/17470218.2016.1195417
    https://doi.org/10.1080/17470218.2016.1195417 [Google Scholar]
  26. Keuleers, E., Lacey, P., Rastle, K., & Brysbaert, M.
    (2012) The British Lexicon Project: Lexical decision data for 28,730 monosyllabic and disyllabic English words. Behavior Research Methods, 44(1), 287–304. 10.3758/s13428‑011‑0118‑4
    https://doi.org/10.3758/s13428-011-0118-4 [Google Scholar]
  27. Kuperman, V., Stadthagen-Gonzalez, H., & Brysbaert, M.
    (2012) Age-of-acquisition ratings for 30,000 English words. Behavior Research Methods, 44(4), 978–990. 10.3758/s13428‑012‑0210‑4
    https://doi.org/10.3758/s13428-012-0210-4 [Google Scholar]
  28. Leech, G., Rayson, P. & Wilson, A.
    (2001) Companion website for: Word Frequencies in Written and Spoken English: based on the British National Corpus. ucrel.lancs.ac.uk/bncfreq/
  29. Marques, J. F., Fonseca, F. L., Morais, S., & Pinto, I. A.
    (2007) Estimated age of acquisition norms for 834 Portuguese nouns and their relation with other psycholinguistic variables. Behavior Research Methods, 39(3), 439–444. 10.3758/BF03193013
    https://doi.org/10.3758/BF03193013 [Google Scholar]
  30. Mikolov, T., Chen, K., Corrado, G., & Dean, J.
    (2013) Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781.
    [Google Scholar]
  31. Mikolov, T., Sutskever, I., Chen, K., Corrado, G. S., & Dean, J.
    (2013) Distributed representations of words and phrases and their compositionality. InAdvances in Neural Information Processing Systems (Neural Information Processing Systems Conference, 2013); pp.3111–3119).
    [Google Scholar]
  32. Northoff, G., Heinzel, A., De Greck, M., Bermpohl, F., Dobrowolny, H., & Panksepp, J.
    (2006) Self-referential processing in our brain – a meta-analysis of imaging studies on the self. Neuroimage, 31(1), 440–457. 10.1016/j.neuroimage.2005.12.002
    https://doi.org/10.1016/j.neuroimage.2005.12.002 [Google Scholar]
  33. Schäfer, S., Wentura, D., & Frings, C.
    (2015) Self-prioritization beyond perception. Experimental Psychology. 10.1027/1618‑3169/a000307
    https://doi.org/10.1027/1618-3169/a000307 [Google Scholar]
  34. Schäfer, S., Frings, C., & Wentura, D.
    (2016) About the composition of self-relevance: Conjunctions not features are bound to the self. Psychonomic Bulletin & Review, 23(3), 887–892. 10.3758/s13423‑015‑0953‑x
    https://doi.org/10.3758/s13423-015-0953-x [Google Scholar]
  35. Shaoul, C. & Westbury, C.
    (2006) USENET Orthographic Frequencies for 111,627 English Words (2005–2006) Edmonton, AB: University of Alberta (downloaded fromwww.psych.ualberta.ca/~westburylab/downloads/wlfreq.download.html
  36. Schmitz, T. W., & Johnson, S. C.
    (2007) Relevance to self: A brief review and framework of neural systems underlying appraisal. Neuroscience & Biobehavioral Reviews, 31(4), 585–596. 10.1016/j.neubiorev.2006.12.003
    https://doi.org/10.1016/j.neubiorev.2006.12.003 [Google Scholar]
  37. Stadthagen-Gonzalez, H., & Davis, C. J.
    (2006) The Bristol norms for age of acquisition, imageability, and familiarity. Behavior Research Methods, 38, 598–605. 10.3758/BF03193891
    https://doi.org/10.3758/BF03193891 [Google Scholar]
  38. Sui, J., He, X., & Humphreys, G. W.
    (2012) Perceptual effects of social salience: Evidence from self-prioritization effects on perceptual matching. Journal of Experimental Psychology: Human Perception and Performance, 38, 1105–1117. 10.1037/a0029792
    https://doi.org/10.1037/a0029792 [Google Scholar]
  39. Symons, C. S., & Johnson, B. T.
    (1997) The self-reference effect in memory: a meta-analysis. Psychological Bulletin, 121(3), 371. 10.1037/0033‑2909.121.3.371
    https://doi.org/10.1037/0033-2909.121.3.371 [Google Scholar]
  40. Tillotson, S. M., Siakaluk, P. D., & Pexman, P. M.
    (2008) Body-object interaction ratings for 1,618 monosyllabic nouns. Behavior Research Methods, 40(4), 1075–1078. 10.3758/BRM.40.4.1075
    https://doi.org/10.3758/BRM.40.4.1075 [Google Scholar]
  41. Westbury, C.
    (2014) You can’t drink a word: Lexical and individual emotionality affect subjective familiarity judgments. Journal of Psycholinguistic Research, 43(5), 631–649. 10.1007/s10936‑013‑9266‑2
    https://doi.org/10.1007/s10936-013-9266-2 [Google Scholar]
  42. (2016) Pay no attention to that man behind the curtain: Explaining semantics without semantics. The Mental Lexicon, 11.3, 350–374. 10.1075/ml.11.3.02wes
    https://doi.org/10.1075/ml.11.3.02wes [Google Scholar]
  43. Westbury, C., & Hollis, G.
    (2018) Conceptualizing syntactic categories as semantic categories: Unifying part-of-speech identification and semantics using co-occurrence vector averaging. Behavior Research Methods, 1–28.
    [Google Scholar]
  44. Westbury, C., Hollis, G., Sidhu, D. M., & Pexman, P. M.
    (2018) Weighing up the evidence for sound symbolism: Distributional properties predict cue strength. Journal of Memory and Language, 99, 122–150. 10.1016/j.jml.2017.09.006
    https://doi.org/10.1016/j.jml.2017.09.006 [Google Scholar]
  45. Westbury, C., & Nicoladis, E.
    (1998) Meaning in children’s first words: Implications for a theory of lexical ontology. InProceedings of the 22nd Annual Boston University Conference on Language Development (pp.768–778). Cascadilla Press: Somerville, MA.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1075/ml.20031.wes
Loading
/content/journals/10.1075/ml.20031.wes
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error