Abstract
Recent studies on linguistics, cognitive science and psychology have shown that describing lexical frequency characteristics can answer many critical questions on language acquisition, mental lexicon and language use. Given the importance of corpus-based methodology, this study reports the preliminary findings from the objective lexical frequency list in TİD based on 103.087 sign tokens. This paper shows that frequency occurrence has a very decisive role on the linguistics categories and language in use. With respect to the multi-functionality of pointing in signed languages, the top ranked ID-gloss occurrences are mostly shaped by the pronominal references. Moreover, when compared to previous studies in terms of lexical density and lexical diversity, TİD shares both similar and different statistical features observed in other signed languages.
7 Acknowledgements
This research was supported in part by a postdoctoral fellowship from the TÜBİTAK BİDEB-2219. TİD Corpus Project was supported by the Turkish Ministry of Family and Social Service. I am grateful to all of our Deaf participants for their contributions to the TİD Corpus project, without them it was impossible to complete this project. I would like to thank the three anonymous reviewers for their insightful comments and efforts in helping me improve the article. Of course, all shortcomings are my own.
List of Abbreviations
- ASL
American Sign Language
- Auslan
Australian Sign Language
- BSL
British Sign Language
- NZSL
New Zealand Sign Language
- SSL
Swedish Sign Language
- TİD
Turkish Sign Language
References
Alderson, J.C. 2007. “Judging the frequency of English words”. Applied Linguistics 28(3). 383–409.10.1093/applin/amm024Search in Google Scholar
Aronoff, M., I. Meir and W. Sandler. 2005. “The paradox of sign language morphology”. Language 81. 301–344.10.1353/lan.2005.0043Search in Google Scholar
Arnon, I. and N. Snider. 2010. “More than words. Frequency effects for multi-word phrases”. Journal of Memory and Language 62. 67–8710.1016/j.jml.2009.09.005Search in Google Scholar
Barlow, M. 2002. “Corpora, concordancing, and language teaching”. Proceedings of the 2002 KAMALL International Conference. Daejon, Korea.Search in Google Scholar
Barlow, M. and S. Kemmer (eds.). 2000. Usage-based models of language. Stanford: CSLI Publications.Search in Google Scholar
Bausch, K. 1979. Modalität und Konjunktivgebrauch in der gesprochenen deutschen Standardsprache: Sprachsystem, Sprachvariation und Sprachwandel im heutigen Deutsch. Max Hueber Verlag: Munich.Search in Google Scholar
Bayyurt, Y. 2010. “A sociolinguistic profile of Turkey, Northern Cyprus and other Turkic states in Central Asia”. In: Ball, M. J. (ed.), The Routledge handbook of sociolinguistics around the world. Routledge: New York. 137–146.10.4324/9780203869659-20Search in Google Scholar
Bock, K. and Z. Griffin. 2000. “Producing words: How mind meets mouth”. In: Wheel-don, L.R. (ed.), Language production. London, UK: Psychology Press. 7–48.Search in Google Scholar
Börstell, C., T. Hörberg and R. Östling. 2016. “Distribution and duration of signs and parts of speech in Swedish Sign Language”. Sign Language & Linguistics, 19(2), 143–196.10.1075/sll.19.2.01borSearch in Google Scholar
Brentari, D. and C. Padden. 2001. “Native and foreign vocabulary in American Sign Language: a lexicon with multiple origins”. In: Brentari, D. (ed.), Foreign vocabulary in sign languages. Mahwah, NJ: Lawrence Erlbaum Associates. 87–120.10.4324/9781410601513Search in Google Scholar
Bybee, J. 1985. Morphology. Amsterdam: John Benjamins.10.1075/tsl.9Search in Google Scholar
Bybee, J. 2001. Phonology and language use. Cambridge, MA: Cambridge University Press.10.1017/CBO9780511612886Search in Google Scholar
Bybee, J. 2002. “Word frequency and context of use in the lexical diffusion of phonetically conditioned sound change”. Language Variation and Change 14. 261–290.10.1093/acprof:oso/9780195301571.003.0011Search in Google Scholar
Bybee, J. 2006. “From usage to grammar: the mind’s response to repetition”. Language 82. 711–733.10.1353/lan.2006.0186Search in Google Scholar
Bybee, J. 2007. Frequency of use and the organization of language. Cambridge: Cambridge University.10.1093/acprof:oso/9780195301571.001.0001Search in Google Scholar
Bybee, J. 2010. Language, usage, and cognition. Cambridge: Cambridge University Press.10.1017/CBO9780511750526Search in Google Scholar
Bybee, J. and J. Scheibman. 1999. “The effect of usage on degree of constituency: the reduction of don’t in American English”. Linguistics 37. 575–596.10.1515/ling.37.4.575Search in Google Scholar
Bybee, J. and P.J. Hopper. 2001. Frequency and the emergence of linguistic structure. Amsterdam: John Benjamins.10.1075/tsl.45Search in Google Scholar
Caselli, N.K., Sehyr, Z.S., Cohen-Goldberg, A. M., and Emmorey, K. 2017. “ASLLEX: A lexical database of American Sign Language”. Behavior Research Methods 49(2), 784–801.10.3758/s13428-016-0742-0Search in Google Scholar
Conlin, F., P. Hagstrom and Neidle, C. 2003. “A particle of indefiniteness in ASL”. Linguistic Discovery 2, 1–21.10.1349/PS1.1537-0852.A.142Search in Google Scholar
Conrad, S. 2005. “Corpus linguistics and L2 teaching”. In: Hinkel, E. (ed.), Handbook of research in second language teaching and learning. Mahwah, NJ: Erlbaum. 393–409.Search in Google Scholar
Cooperrider K, N. Abner and Goldin-Meadow S. 2018. “The palm-up puzzle: meanings and origins of a widespread form in gesture and sign”. Frontiers in Communication. 3:23.10.3389/fcomm.2018.00023Search in Google Scholar
Cormier, K., J. Fenlon, T. Johnston, R. Rentelis, A. Schembri, K. Rowley, R. Adam and B. Woll. 2012a. “From corpus to lexical database to online dictionary: Issues in annotation of the BSL Corpus and the development of BSL SignBank”. In: Crasborn, O., E. Efthimiou, E. Fotinea, T. Hanke, J. Kristoffersen and J. Mesch (eds.), Proceedings of the 5th Workshop on the Representation and Processing of Sign Languages: Interactions between Corpus and Lexicon [Language Resources and Evaluation Conference (LREC)] (pp. 5–12). Paris France: European Language Resources Association (ELRA).Search in Google Scholar
Cormier, K., A. Schembri, D. Vinson and E. Orfanidou. 2012b. “First language acquisition differs from second language acquisition in prelingually deaf signers: Evidence from sensitivity to grammatical judgement in British Sign Language”. Cognition 124(1). 50–65.10.1016/j.cognition.2012.04.003Search in Google Scholar
Cormier, K., A. Schembri and B. Woll. 2013. “Pronouns and pointing in sign languages”. Lingua: International Review of General Linguistics 137. 230–247.10.1016/j.lingua.2013.09.010Search in Google Scholar
Cormier, K., O. Crasborn and R. Bank. 2016. “Digging into Signs: Emerging Annotation Standards for Sign Language Corpora”. In: Workshop Proceedings 7th Workshop on the Representation and Processing of Sign Languages: Corpus Mining. ELRA. 35–40.Search in Google Scholar
Dell, G.S. 1990. “Effects of frequency and vocabulary type on phonological speech errors”. Language & Cognitive Processes 5. 313–349.10.1080/01690969008407066Search in Google Scholar
Diessel, H. 2004. The acquisition of complex sentences. Cambridge, MA: Cambridge University Press.10.1017/CBO9780511486531Search in Google Scholar
Diessel, H. 2007. “Frequency effects in language acquisition, language use, and diachronic change”. New Ideas in Psychology 25. 108–127.10.1016/j.newideapsych.2007.02.002Search in Google Scholar
Dikyuva, H., B. Makaroğlu and E. Arık. 2017. Turkish Sign Language grammar. Ankara: Ministry of Family and Social Policies Press.Search in Google Scholar
Dinkin, A. 2007. “The real effect of word frequency on phonetic variation”. Paper Presented at the 31st Penn Linguistics Colloquium, Philadelphia, PA.Search in Google Scholar
Ellis, N. C. 2002. “Frequency effects in language processing: A review with implications for theories of implicit and explicit language acquisition”. Studies in Second Language Acquisition 24. 143–188.10.1017/S0272263102002024Search in Google Scholar
Emmorey, K.D. 2002. Language, cognition, and the brain: Insights from sign language research. Mahwah, NJ: Lawrence Erlbaum Associates.10.4324/9781410603982Search in Google Scholar
Engberg-Pedersen, E. 2002. “Gesture in signing: the presentation gesture in Danish Sign Language”. In: Schulmeister R. and H. Reinitzer (eds.) Progress in Sign Language Research: in Honor of Siegmund Prilwitz. Hamburg: Signum. 143–162.Search in Google Scholar
Fenlon, J., A. Schembri, R. Rentelis, D. Vinson and K. Cormier. 2014. “Using conversational data to determine lexical frequency in British Sign Language: The influence of text type”. Lingua 143. 187–202.10.1016/j.lingua.2014.02.003Search in Google Scholar
Fenlon, J., A. Schembri, T. Johnston and K. Cormier. 2015. “Documentary and corpus approaches to sign language research”. In: Orfanidou, E., B. Woll and G. Morgan (eds.), Research methods in sign language studies: A practical guide. Hoboken: John Wiley & Sons, Inc. 157–169.10.1002/9781118346013.ch10Search in Google Scholar
File-Muriel, R.J. 2010. “Lexical frequency as a scalar variable in explaining variation”. Canadian Journal of Linguistics 55. 1–25.10.1017/S0008413100001353Search in Google Scholar
Gabarró-López, S. (2020). Are discourse markers related to age and educational background? A comparative account between two sign languages. Journal of Pragmatics, 156, 68-82.10.1016/j.pragma.2018.12.019Search in Google Scholar
Gardner, M.K., E.Z. Rothkopf, R. Lapan and T. Lafferty. 1987. “The word frequency effect in lexical decision: Finding a frequency based component”. Memory & Cognition 15. 24–28.10.3758/BF03197709Search in Google Scholar
Givón, T. 1979. On understanding grammar. New York: Academic Press.Search in Google Scholar
Goldberg, A.E. 2006. Constructions at work. The nature of generalization in language. Oxford: Oxford University Press.10.1093/acprof:oso/9780199268511.001.0001Search in Google Scholar
Hanke, T. 2016. “Towards a visual sign language corpus linguistics”. In: Workshop Proceedings 7th Workshop on the Representation and Processing of Sign Languages: Corpus Mining. ELRA. 89–92.Search in Google Scholar
Hochgesang, J. A. 2019. “Tyranny of glossing revisited: reconsidering representational practices of signed languages via best practices of data citation”. Presented at TISLR13, the 13th Conference of Theoretical Issues in Sign Language Research, Hamburg, Germany (September 26–28, 2019).Search in Google Scholar
Hopper, P.J. 1987. “Emergent grammar”. Berkeley Linguistics Society 13. 139–157.10.3765/bls.v13i0.1834Search in Google Scholar
Hou, L., J.P. Morford. 2020. “Using signed language collocations to investigate acquisition: A commentary on Ambridge (2020)”. First Language10.1177/0142723720908075Search in Google Scholar
Hoza, J. 2011. “The discourse and politeness functions of HEY and WELL in American Sign Language”. In: Roy, C.B. (ed.), Discourse in signed languages, sociolinguistics in deaf communities series 17. Washington, D.C: Gallaudet University Press. 70–95.Search in Google Scholar
Johnston, T. 2010. “From archive to corpus: Transcription and annotation in the creation of signed language corpora”. International Journal of Corpus Linguistics, 15(1). 106–131.10.1075/ijcl.15.1.05johSearch in Google Scholar
Johnston, T. 2012. “Lexical frequency in sign languages”. Journal of Deaf Studies and Education 17, 163–193.10.1093/deafed/enr036Search in Google Scholar
Kidd, E., Lieven, E. V. M., and Tomasello, M. 2010. “Lexical frequency and exemplar-based learning effects in language acquisition: evidence from sentential complements”. Language Sciences 32(1). 132–142.10.1016/j.langsci.2009.05.002Search in Google Scholar
Kitzinger, J. (1994). The methodology of focus groups: the importance of interaction between research participants. Sociology of health & illness, 16(1), 103-121.10.1111/1467-9566.ep11347023Search in Google Scholar
Krug, M. 2003. “Frequency as a determinant of grammatical variation and change”. In: Rohdenburg, G. and B. Mondorf (eds.), Determinants of grammatical variation in English. Berlin: Mouton de Gruyter. 7–67.10.1515/9783110900019.7Search in Google Scholar
Kucera, H. and W. Francis. 1967. Computational analysis of present-day American English. Providence, RI: Brown University Press.Search in Google Scholar
Lakoff, G. 1987. Women, fire, and dangerous things. Chicago: Chicago University Press.10.7208/chicago/9780226471013.001.0001Search in Google Scholar
Langacker, R.W. 2009. “A dynamic view of usage and language acquisition”. Cognitive Linguistics 20. 627–640.10.1515/COGL.2009.027Search in Google Scholar
Langacker, R.W. 1987. Foundations of cognitive grammar, vol. II: Theoretical prerequisites. Stanford: Stanford University Press.Search in Google Scholar
Leech, G., P. Rayson and A. Wilson. 2001. Word frequencies in written and spoken English based on the British national corpus. London: Longman.Search in Google Scholar
Lepic, R. 2019. “A usage-based alternative to “lexicalization” in sign language linguistics”. Glossa: A Journal of General Linguistics, 4(1). 23. 1–30.10.5334/gjgl.840Search in Google Scholar
MacWhinney, B. (ed.). 1999. The emergence of language. Hillsdale, NJ: Erlbaum.Search in Google Scholar
Makaroğlu, B. and H. Dikyuva (eds.). 2017. The contemporary Turkish Sign Language dictionary. Ankara: The Turkish Ministry of Family and Social Policy. Retrieved from <http://tidsozluk.net>.Search in Google Scholar
Marian, V., H.K. Blumenfeld and M. Kaushanskaya. 2007. “The Language experience and proficiency questionnaire (LEAP-Q): Assessing language profiles in bilinguals and multilinguals”. Journal of Speech, Language, and Hearing Research, 50. 940–967.10.1044/1092-4388(2007/067)Search in Google Scholar
Mathur, G. and C. Rathmann. 2006. “Variability in verbal agreement forms across four signed languages”. In: Goldstein, L., D. Whalen and C. T. Best (eds.), Laboratory phonology VIII. Berlin: Mouton. 287–314.10.1515/9783110197211.1.287Search in Google Scholar
Mayberry, R.I., M.L. Hall and M. Zvaigzne. 2014. “Subjective frequency ratings for 432 ASL signs”. Behavior Research Methods 46(2). 526–539.10.3758/s13428-013-0370-xSearch in Google Scholar
Meier, R.P. 1990. “Person deixis in ASL”. In: Fischer, S.D. and P. Siple (eds.), Theoretical Issues in Sign Language Research. Linguistics, vol. 1. University of Chicago Press, Chicago. 175–190.Search in Google Scholar
Mesch, J. and L. Wallin. 2015. “Gloss annotations in the Swedish Sign Language corpus”. International Journal of Corpus Linguistics 20(1). 102–120.10.1075/ijcl.20.1.05mesSearch in Google Scholar
Metzger, M. and B. Bahan. 2001. “Discourse analysis”. In: Lucas, C. (ed.), The sociolinguistics of sign languages. Cambridge: Cambridge University Press. 112–144.10.1017/CBO9780511612824.007Search in Google Scholar
McKee, D. and G. Kennedy. 2006. “The distribution of signs in New Zealand Sign Language”. Sign Language Studies 6(4). 372–390.10.1353/sls.2006.0027Search in Google Scholar
Morford, J. and J. MacFarlane. 2003. “Frequency characteristics of American Sign Language”. Sign Language Studies 3. 213–225.10.1353/sls.2003.0003Search in Google Scholar
Nation, I. 2004. “A study of the most frequent word families in the British national corpus”. In: Bogaards, P. and B. Laufer (eds.), Vocabulary in a second language: selection, acquisition and testing. Amsterdam: John Benjamins. 3–13.10.1075/lllt.10.03natSearch in Google Scholar
Nation, P. 2001. Learning vocabulary in another language. Cambridge, UK: Cambridge University Press.10.1017/CBO9781139524759Search in Google Scholar
Özsoy, A.S., M. Kelepir, D. Nuhbalaoğlu and E. Hakgüder. 2014. “Commands in Turkish Sign Language”. 言語研究 (Gengo Kenkyu) 146. 13–30.Search in Google Scholar
Philips, B. 1984. “Word frequency and the actuation of sound change”. Language 60, 320-342.10.2307/413643Search in Google Scholar
Quer, J. and M. Steinbach. 2019. “Handling sign language data: the impact of modality”. Frontiers in psychology 10. 483.10.3389/fpsyg.2019.00483Search in Google Scholar
Rayson, P. and R. Garside. 2000. “Comparing corpora using frequency profiling”. In: Proceedings of the workshop on Comparing Corpora. Association for Computational Linguistics. 1–6.10.3115/1117729.1117730Search in Google Scholar
Schembri, A., J. Fenlon, R. Rentelis, S. Reynolds and K. Cormier. 2013. “Building the British sign language corpus”. Language Documentation & Conservation 7. 136–154.Search in Google Scholar
Slobin, D.I. 2008. “Breaking the molds: Signed languages and the nature of human language”. Sign Language Studies 8(2). 114–13010.1353/sls.2008.0004Search in Google Scholar
Sloetjes, H. and P. Wittenburg. 2018. ELAN (version 5.2). Nijmegen: Max Planck Institute for Psycholinguistics. Retrieved from <https://tla.mpi.nl/tools/tla-tools/elan/>.Search in Google Scholar
Talmy, L. 1983. “How language structure space”. In: Pick H.L. and L.P. Acredolo (eds.), Spatial orientation: Theory, research, and application. New York: Plenum Press. 225–282.10.1007/978-1-4615-9325-6_11Search in Google Scholar
Taylor, J. R. (2002). Cognitive grammar. Oxford, UK: Oxford University Press.10.1093/oso/9780198700333.001.0001Search in Google Scholar
Vinson, D.P., K. Cormier, T. Denmark, A. Schembri and G. Vigliocco. 2008. “The British Sign Language (BSL) norms for age of acquisition, familiarity, and iconicity”. Behavior Research Methods 40(4). 1079–1087.10.3758/BRM.40.4.1079Search in Google Scholar
Wilkinson, E. 2016. “Finding frequency effects in the usage of NOT collocations in American Sign Language”. Sign Language & Linguistics, 19(1). 82–123.10.1075/sll.19.1.03wilSearch in Google Scholar
Zeshan, U. 2006. “Negative and interrogative structures in Turkish Sign Language (TİD)”. In Zeshan U. (ed.) Interrogative and Negative Constructions in Sign Languages. Nijmegen: Ishara Press. 128–164.10.26530/OAPEN_453832Search in Google Scholar
Zipf, G.K. 1945/1949. Human behaviour and the principle of least effort. Reading, MA: Addison Wesley Publishing co.Search in Google Scholar
Rank order of 300 frequent signs in TİD (approx. 69 percent of the signs in the TİD corpus).
| Rank | ID-gloss | N | Per (1000) | % Database | % Cumulative |
|---|---|---|---|---|---|
| 1 | PT:PRO1 | 8398 | 81.5 | 8.15% | 8.15% |
| 2 | PT:PRO2/3 | 5729 | 55.6 | 5.56% | 13.71% |
| 3 | PT:LOC | 1494 | 14.5 | 1.45% | 15.16% |
| 4 | GO | 1333 | 12.9 | 1.29% | 16.45% |
| 5 | KNOW | 1157 | 11.2 | 1.12% | 17.57% |
| 6 | HAVE | 1133 | 11.0 | 1.10% | 18.67% |
| 7 | TO BE | 1088 | 10.6 | 1.06% | 19.73% |
| 8 | HAVE-NOT | 1032 | 10.0 | 1.00% | 20.73% |
| 9 | WHAT | 939 | 9.1 | 0.91% | 21.64% |
| 10 | DEAF1/2 | 873 | 8.5 | 0.85% | 22.49% |
| 11 | UNDERSTAND | 844 | 8.2 | 0.82% | 23.31% |
| 12 | LOOK | 801 | 7.8 | 0.78% | 24.09% |
| 13 | GOOD | 783 | 7.6 | 0.76% | 24.85% |
| 14 | SAY | 759 | 7.4 | 0.74% | 25.59% |
| 15 | SIGN | 705 | 6.8 | 0.68% | 26.27% |
| 16 | YES1 | 687 | 6.7 | 0.67% | 26.94% |
| 17 | GIVE | 685 | 6.6 | 0.66% | 27.60% |
| 18 | COME | 677 | 6.6 | 0.66% | 28.26% |
| 19 | DO1/2 | 661 | 6.4 | 0.64% | 28.90% |
| 20 | FOR | 589 | 5.7 | 0.57% | 29.47% |
| 21 | FATHER | 560 | 5.4 | 0.54% | 30.01% |
| 22 | OLD | 498 | 4.8 | 0.48% | 30.49% |
| 23 | SAME-LOC | 496 | 4.8 | 0.48% | 30.97% |
| 24 | ALL-LOC | 489 | 4.7 | 0.47% | 31.44% |
| 25 | FINISH | 481 | 4.7 | 0.47% | 31.91% |
| 26 | PALM-UP:WELL | 479 | 4.6 | 0.46% | 32.37% |
| 27 | DIFFICULT | 476 | 4.6 | 0.46% | 32.83% |
| 28 | SPEAK-2PERSON | 470 | 4.6 | 0.46% | 33.29% |
| 29 | WANT | 455 | 4.4 | 0.44% | 33.73% |
| 30 | NEVER | 455 | 4.4 | 0.44% | 34.18% |
| 31 | MOTHER | 439 | 4.3 | 0.43% | 34.60% |
| 32 | EAT/FOOD | 437 | 4.2 | 0.42% | 35.03% |
| 33 | PERSON | 433 | 4.2 | 0.42% | 35.45% |
| 34 | SCHOOL | 421 | 4.1 | 0.41% | 35.85% |
| 35 | NAME1/2 | 419 | 4.1 | 0.41% | 36.26% |
| 36 | SHOULD | 417 | 4.0 | 0.40% | 36.66% |
| 37 | CAR | 414 | 4.0 | 0.40% | 37.06% |
| 38 | NOW | 403 | 3.9 | 0.39% | 37.45% |
| 39 | MONEY | 379 | 3.7 | 0.37% | 37.82% |
| 40 | SEE | 378 | 3.7 | 0.37% | 38.19% |
| 41 | LOVE | 376 | 3.6 | 0.36% | 38.55% |
| 42 | WORK1 | 370 | 3.6 | 0.36% | 38.91% |
| 43 | YEAR | 369 | 3.6 | 0.36% | 39.26% |
| 44 | HEAD | 359 | 3.5 | 0.35% | 39.61% |
| 45 | N:ONE | 349 | 3.4 | 0.34% | 39.95% |
| 46 | NOT | 345 | 3.3 | 0.33% | 40.28% |
| 47 | TELEPHONE | 342 | 3.3 | 0.33% | 40.61% |
| 48 | VERY | 334 | 3.2 | 0.32% | 40.94% |
| 49 | N:THREE1 | 331 | 3.2 | 0.32% | 41.25% |
| 50 | FRIEND | 328 | 3.2 | 0.32% | 41.57% |
| 51 | TAKE | 326 | 3.2 | 0.32% | 41.89% |
| 52 | PUT | 320 | 3.1 | 0.31% | 42.20% |
| 53 | SPECIAL | 314 | 3.0 | 0.30% | 42.50% |
| 54 | SELF | 313 | 3.0 | 0.30% | 42.80% |
| 55 | COMFORTABLE | 299 | 2.9 | 0.29% | 43.09% |
| 56 | WATCH | 297 | 2.9 | 0.29% | 43.38% |
| 57 | WRITE | 290 | 2.8 | 0.28% | 43.66% |
| 58 | BEFORE1/2 | 287 | 2.8 | 0.28% | 43.94% |
| 59 | GIRL | 281 | 2.7 | 0.27% | 44.21% |
| 60 | BOOK1/2 | 272 | 2.6 | 0.26% | 44.48% |
| 61 | ALWAYS | 258 | 2.5 | 0.25% | 44.73% |
| 62 | DOCTOR | 255 | 2.5 | 0.25% | 44.98% |
| 63 | TRUE | 253 | 2.5 | 0.25% | 45.22% |
| 64 | OKAY | 250 | 2.4 | 0.24% | 45.46% |
| 65 | MORE | 250 | 2.4 | 0.24% | 45.71% |
| 66 | FULL | 246 | 2.4 | 0.24% | 45.95% |
| 67 | PROBLEM | 245 | 2.4 | 0.24% | 46.18% |
| 68 | HOME | 242 | 2.3 | 0.23% | 46.41% |
| 69 | FAMILY | 239 | 2.3 | 0.23% | 46.65% |
| 70 | EXPLAIN | 237 | 2.3 | 0.23% | 46.88% |
| 71 | SENTENCE | 232 | 2.3 | 0.23% | 47.10% |
| 72 | N: FOUR | 230 | 2.2 | 0.22% | 47.32% |
| 73 | LITTLE | 226 | 2.2 | 0.22% | 47.54% |
| 74 | MUST | 225 | 2.2 | 0.22% | 47.76% |
| 75 | LATER | 223 | 2.2 | 0.22% | 47.97% |
| 76 | TOGETHER | 219 | 2.1 | 0.21% | 48.19% |
| 77 | EVERYBODY | 219 | 2.1 | 0.21% | 48.40% |
| 78 | CAN | 218 | 2.1 | 0.21% | 48.61% |
| 79 | TIME | 216 | 2.1 | 0.21% | 48.82% |
| 80 | AS IF/LIKE | 215 | 2.1 | 0.21% | 49.03% |
| 81 | CALL | 215 | 2.1 | 0.21% | 49.24% |
| 82 | TRAVEL | 212 | 2.1 | 0.21% | 49.44% |
| 83 | SICK1/2 | 210 | 2.0 | 0.20% | 49.65% |
| 84 | ACCORDING TO | 207 | 2.0 | 0.20% | 49.85% |
| 85 | WORK2 | 206 | 2.0 | 0.20% | 50.05% |
| 86 | HAPPEN | 203 | 2.0 | 0.20% | 50.24% |
| 87 | THINK | 200 | 1.9 | 0.19% | 50.44% |
| 88 | TEACHER1/2 | 197 | 1.9 | 0.19% | 50.63% |
| 89 | SUPER | 192 | 1.9 | 0.19% | 50.82% |
| 90 | ROAD | 191 | 1.9 | 0.19% | 51.00% |
| 91 | FIND | 179 | 1.7 | 0.17% | 51.17% |
| 92 | IMPORTANT | 176 | 1.7 | 0.17% | 51.34% |
| 93 | ASK | 176 | 1.7 | 0.17% | 51.51% |
| 94 | BUT | 176 | 1.7 | 0.17% | 51.68% |
| 95 | STOP2 | 171 | 1.7 | 0.17% | 51.85% |
| 96 | FILM | 171 | 1.7 | 0.17% | 52.02% |
| 97 | PLACE | 163 | 1.6 | 0.16% | 52.17% |
| 98 | WATER | 162 | 1.6 | 0.16% | 52.33% |
| 99 | INTERPRETER | 159 | 1.5 | 0.15% | 52.48% |
| 100 | DIFFERENCE | 156 | 1.5 | 0.15% | 52.64% |
| 101 | LESS | 156 | 1.5 | 0.15% | 52.79% |
| 102 | CL:GO-PERSON | 155 | 1.5 | 0.15% | 52.94% |
| 103 | N:TWO | 155 | 1.5 | 0.15% | 53.09% |
| 104 | BROTHER | 153 | 1.5 | 0.15% | 53.23% |
| 105 | HEAR | 152 | 1.5 | 0.15% | 53.38% |
| 106 | READ | 151 | 1.5 | 0.15% | 53.53% |
| 107 | GROUP | 150 | 1.5 | 0.15% | 53.67% |
| 108 | NEW | 150 | 1.5 | 0.15% | 53.82% |
| 109 | WAIT | 148 | 1.4 | 0.14% | 53.96% |
| 110 | EDUCATION | 148 | 1.4 | 0.14% | 54.11% |
| 111 | LEARN | 148 | 1.4 | 0.14% | 54.25% |
| 112 | WRONG | 147 | 1.4 | 0.14% | 54.39% |
| 113 | AGE | 144 | 1.4 | 0.14% | 54.53% |
| 114 | ENTER | 142 | 1.4 | 0.14% | 54.67% |
| 115 | MARRY | 142 | 1.4 | 0.14% | 54.81% |
| 116 | PARTNER | 138 | 1.3 | 0.13% | 54.94% |
| 117 | SIT | 135 | 1.3 | 0.13% | 55.08% |
| 118 | PAPER | 134 | 1.3 | 0.13% | 55.21% |
| 119 | GET USED TO | 134 | 1.3 | 0.13% | 55.34% |
| 120 | WALK | 133 | 1.3 | 0.13% | 55.46% |
| 121 | COMMUNICATION | 132 | 1.3 | 0.13% | 55.59% |
| 122 | FOR EXAMPLE | 129 | 1.3 | 0.13% | 55.72% |
| 123 | BE QUIET | 129 | 1.3 | 0.13% | 55.85% |
| 124 | MUCH | 128 | 1.2 | 0.12% | 55.97% |
| 125 | CANNOT | 128 | 1.2 | 0.12% | 56.09% |
| 126 | DAY | 126 | 1.2 | 0.12% | 56.21% |
| 127 | PLAY | 125 | 1.2 | 0.12% | 56.33% |
| 128 | PAST | 125 | 1.2 | 0.12% | 56.45% |
| 129 | LEAVE | 124 | 1.2 | 0.12% | 56.57% |
| 130 | EASY | 123 | 1.2 | 0.12% | 56.69% |
| 131 | AIRPLANE | 122 | 1.2 | 0.12% | 56.81% |
| 132 | SOMETHING | 121 | 1.2 | 0.12% | 56.93% |
| 133 | VARIOUS | 120 | 1.2 | 0.12% | 57.05% |
| 134 | RESCUE | 119 | 1.2 | 0.12% | 57.17% |
| 135 | THAT'S WHY | 119 | 1.2 | 0.12% | 57.29% |
| 136 | GOD | 118 | 1.1 | 0.11% | 57.40% |
| 137 | N:SECOND | 117 | 1.1 | 0.11% | 57.51% |
| 138 | WHERE | 112 | 1.1 | 0.11% | 57.62% |
| 139 | TELEVISION | 111 | 1.1 | 0.11% | 57.73% |
| 140 | MINUTE | 111 | 1.1 | 0.11% | 57.84% |
| 141 | NO | 111 | 1.1 | 0.11% | 57.95% |
| 142 | APPROPRIATE | 110 | 1.1 | 0.11% | 58.06% |
| 143 | COUNTRY | 108 | 1.0 | 0.10% | 58.16% |
| 144 | CL: SHORT-THIN | 108 | 1.0 | 0.10% | 58.26% |
| 145 | COMPUTER | 108 | 1.0 | 0.10% | 58.36% |
| 146 | FACE | 108 | 1.0 | 0.10% | 58.46% |
| 147 | MONTH | 107 | 1.0 | 0.10% | 58.56% |
| 148 | VOTE | 105 | 1.0 | 0.10% | 58.66% |
| 149 | END | 105 | 1.0 | 0.10% | 58.76% |
| 150 | TO BE PLEASED | 105 | 1.0 | 0.10% | 58.86% |
| 151 | FIRST | 104 | 1.0 | 0.10% | 58.96% |
| 152 | WIN | 104 | 1.0 | 0.10% | 59.06% |
| 153 | PT: POSS2/3 | 104 | 1.0 | 0.10% | 59.16% |
| 154 | NOT TO BOTHER | 103 | 1.0 | 0.10% | 59.26% |
| 155 | SPORT | 100 | 1.0 | 0.10% | 59.36% |
| 156 | SEA | 98 | 1.0 | 0.10% | 59.46% |
| 157 | UNIVERSITY | 97 | 0.9 | 0.09% | 59.55% |
| 158 | N:THREE2 | 97 | 0.9 | 0.09% | 59.64% |
| 159 | TOURISM | 96 | 0.9 | 0.09% | 59.73% |
| 160 | ENJOY | 95 | 0.9 | 0.09% | 59.82% |
| 161 | AND | 94 | 0.9 | 0.09% | 59.91% |
| 162 | BE CAREFUL | 93 | 0.9 | 0.09% | 60.00% |
| 163 | PT:BACK-LOC | 93 | 0.9 | 0.09% | 60.09% |
| 164 | DIE | 91 | 0.9 | 0.09% | 60.18% |
| 165 | ADVERTISEMENT | 91 | 0.9 | 0.09% | 60.27% |
| 166 | TEST | 90 | 0.9 | 0.09% | 60.36% |
| 167 | WHY | 89 | 0.9 | 0.09% | 60.45% |
| 168 | OPEN | 88 | 0.9 | 0.09% | 60.54% |
| 169 | PT:PRO-PL2/3 | 88 | 0.9 | 0.09% | 60.63% |
| 170 | TASTE | 88 | 0.9 | 0.09% | 60.72% |
| 171 | SLEEP | 86 | 0.8 | 0.08% | 60.80% |
| 172 | HAPPY | 85 | 0.8 | 0.08% | 60.88% |
| 173 | REMEMBER | 84 | 0.8 | 0.08% | 60.96% |
| 174 | FORGET | 84 | 0.8 | 0.08% | 61.04% |
| 175 | STAY | 83 | 0.8 | 0.08% | 61.12% |
| 176 | HOW | 82 | 0.8 | 0.08% | 61.20% |
| 177 | BATTLE | 82 | 0.8 | 0.08% | 61.28% |
| 178 | SUPPORT | 82 | 0.8 | 0.08% | 61.36% |
| 179 | COLLEGE | 81 | 0.8 | 0.08% | 61.44% |
| 180 | REASON | 80 | 0.8 | 0.08% | 61.52% |
| 181 | QUICK | 80 | 0.8 | 0.08% | 61.60% |
| 182 | FREE | 80 | 0.8 | 0.08% | 61.68% |
| 183 | CULTURE | 80 | 0.8 | 0.08% | 61.76% |
| 184 | EYE | 79 | 0.8 | 0.08% | 61.84% |
| 185 | GOVERNMENT | 79 | 0.8 | 0.08% | 61.92% |
| 186 | CL: PERSON-PASS BY | 78 | 0.8 | 0.08% | 62.00% |
| 187 | LITTLE-AGE | 77 | 0.7 | 0.07% | 62.07% |
| 188 | PUNCH | 77 | 0.7 | 0.07% | 62.14% |
| 189 | FISH | 77 | 0.7 | 0.07% | 62.21% |
| 190 | MORAL | 77 | 0.7 | 0.07% | 62.28% |
| 191 | MUSLIM | 77 | 0.7 | 0.07% | 62.35% |
| 192 | PT: HERE-LOC | 76 | 0.7 | 0.07% | 62.42% |
| 193 | HEAD/CHAIRMAN | 75 | 0.7 | 0.07% | 62.49% |
| 194 | SO | 74 | 0.7 | 0.07% | 62.56% |
| 195 | HOLD | 74 | 0.7 | 0.07% | 62.63% |
| 196 | HOW MANY | 74 | 0.7 | 0.07% | 62.70% |
| 197 | DAMAGE | 74 | 0.7 | 0.07% | 62.77% |
| 198 | BE SATISFIED | 73 | 0.7 | 0.07% | 62.84% |
| 199 | RELAX | 73 | 0.7 | 0.07% | 62.91% |
| 200 | FEAR | 72 | 0.7 | 0.07% | 62.98% |
| 201 | NEWS | 71 | 0.7 | 0.07% | 63.05% |
| 202 | HOPEFULLY | 71 | 0.7 | 0.07% | 63.12% |
| 203 | CL:FLAT-HALF | 71 | 0.7 | 0.07% | 63.19% |
| 204 | SURPRISE | 71 | 0.7 | 0.07% | 63.26% |
| 205 | ASSOCIATION | 71 | 0.7 | 0.07% | 63.33% |
| 206 | DISABLED | 71 | 0.7 | 0.07% | 63.40% |
| 207 | ELECTION | 71 | 0.7 | 0.07% | 63.47% |
| 208 | LUCK | 70 | 0.7 | 0.07% | 63.54% |
| 209 | GET BORED | 69 | 0.7 | 0.07% | 63.61% |
| 210 | PAY | 69 | 0.7 | 0.07% | 63.68% |
| 211 | SCREEN | 69 | 0.7 | 0.07% | 63.75% |
| 212 | TRAFFIC | 69 | 0.7 | 0.07% | 63.82% |
| 213 | NIGHT | 69 | 0.7 | 0.07% | 63.89% |
| 214 | RESEARCH | 69 | 0.7 | 0.07% | 63.96% |
| 215 | PHOTOGRAPH | 68 | 0.7 | 0.07% | 64.03% |
| 216 | CHANGE | 68 | 0.7 | 0.07% | 64.10% |
| 217 | Turkish | 68 | 0.7 | 0.07% | 64.17% |
| 218 | ARRIVE | 68 | 0.7 | 0.07% | 64.24% |
| 219 | CL:HEAVY | 67 | 0.6 | 0.06% | 64.30% |
| 220 | SECURITY | 67 | 0.6 | 0.06% | 64.36% |
| 221 | N: FIRST | 67 | 0.6 | 0.06% | 64.42% |
| 222 | HARD | 66 | 0.6 | 0.06% | 64.48% |
| 223 | START | 66 | 0.6 | 0.06% | 64.54% |
| 224 | COME ON | 66 | 0.6 | 0.06% | 64.60% |
| 225 | IMPOSSIBLE | 65 | 0.6 | 0.06% | 64.66% |
| 226 | SINGLE | 65 | 0.6 | 0.06% | 64.72% |
| 227 | GUEST | 65 | 0.6 | 0.06% | 64.78% |
| 228 | AT ONCE1 | 64 | 0.6 | 0.06% | 64.84% |
| 229 | GRADUATE | 64 | 0.6 | 0.06% | 64.90% |
| 230 | PLEASURE | 64 | 0.6 | 0.06% | 64.96% |
| 231 | N: THIRD | 64 | 0.6 | 0.06% | 65.02% |
| 232 | MAN1 | 63 | 0.6 | 0.06% | 65.08% |
| 233 | ARM | 63 | 0.6 | 0.06% | 65.14% |
| 234 | WHO | 63 | 0.6 | 0.06% | 65.20% |
| 235 | DOOR | 63 | 0.6 | 0.06% | 65.26% |
| 236 | CLASSROOM | 62 | 0.6 | 0.06% | 65.32% |
| 237 | SUBTITLE | 62 | 0.6 | 0.06% | 65.38% |
| 238 | EAR | 62 | 0.6 | 0.06% | 65.44% |
| 239 | BRIDGE | 62 | 0.6 | 0.06% | 65.50% |
| 240 | AGAIN | 62 | 0.6 | 0.06% | 65.56% |
| 241 | ANYWAY | 62 | 0.6 | 0.06% | 65.62% |
| 242 | GROW UP | 61 | 0.6 | 0.06% | 65.68% |
| 243 | CAMERA | 61 | 0.6 | 0.06% | 65.74% |
| 244 | HEART | 61 | 0.6 | 0.06% | 65.80% |
| 245 | ALSO | 61 | 0.6 | 0.06% | 65.86% |
| 246 | LACKING | 61 | 0.6 | 0.06% | 65.92% |
| 247 | EMPTY | 60 | 0.6 | 0.06% | 65.98% |
| 248 | GRANDFATHER | 60 | 0.6 | 0.06% | 66.04% |
| 249 | EXPERT | 60 | 0.6 | 0.06% | 66.10% |
| 250 | MISTAKE | 60 | 0.6 | 0.06% | 66.16% |
| 251 | TOPIC | 60 | 0.6 | 0.06% | 66.22% |
| 252 | CL:SMALL | 59 | 0.6 | 0.06% | 66.28% |
| 253 | SON | 59 | 0.6 | 0.06% | 66.34% |
| 254 | DISTANT | 59 | 0.6 | 0.06% | 66.40% |
| 255 | OUTSIDE | 58 | 0.6 | 0.06% | 66.46% |
| 256 | WEEK | 58 | 0.6 | 0.06% | 66.52% |
| 257 | BEAT | 58 | 0.6 | 0.06% | 66.58% |
| 258 | CHAT | 57 | 0.6 | 0.06% | 66.64% |
| 259 | CHOOSE | 57 | 0.6 | 0.06% | 66.70% |
| 260 | REMOTE CONTROL | 57 | 0.6 | 0.06% | 66.76% |
| 261 | CL:SHOW | 56 | 0.5 | 0.05% | 66.81% |
| 262 | CL:PAINTING | 56 | 0.5 | 0.05% | 66.86% |
| 263 | BIRTH | 56 | 0.5 | 0.05% | 66.91% |
| 264 | TIME | 55 | 0.5 | 0.05% | 66.96% |
| 265 | BUS | 55 | 0.5 | 0.05% | 67.01% |
| 266 | WEATHER | 55 | 0.5 | 0.05% | 67.06% |
| 267 | CL: MEET | 55 | 0.5 | 0.05% | 67.11% |
| 268 | CHILD | 54 | 0.5 | 0.05% | 67.16% |
| 269 | THANKSGIVING | 54 | 0.5 | 0.05% | 67.21% |
| 270 | LONG | 54 | 0.5 | 0.05% | 67.26% |
| 271 | BAN | 54 | 0.5 | 0.05% | 67.31% |
| 272 | MAYBE | 54 | 0.5 | 0.05% | 67.36% |
| 273 | IDEA | 54 | 0.5 | 0.05% | 67.41% |
| 274 | N: ZERO | 54 | 0.5 | 0.05% | 67.46% |
| 275 | LOVE | 54 | 0.5 | 0.05% | 67.51% |
| 276 | WONDER | 53 | 0.5 | 0.05% | 67.56% |
| 277 | INCREASE | 53 | 0.5 | 0.05% | 67.61% |
| 278 | COME TO MIND | 53 | 0.5 | 0.05% | 67.66% |
| 279 | MUNICIPAL | 53 | 0.5 | 0.05% | 67.71% |
| 280 | BAD | 53 | 0.5 | 0.05% | 67.76% |
| 281 | SEND | 52 | 0.5 | 0.05% | 67.81% |
| 282 | MORNING | 52 | 0.5 | 0.05% | 67.86% |
| 283 | BE SAD | 52 | 0.5 | 0.05% | 67.91% |
| 284 | SO AND SO | 52 | 0.5 | 0.05% | 67.96% |
| 285 | SOUND | 51 | 0.5 | 0.05% | 68.01% |
| 286 | MAN2 | 51 | 0.5 | 0.05% | 68.06% |
| 287 | SHOUT | 51 | 0.5 | 0.05% | 68.11% |
| 288 | NEAR BY | 51 | 0.5 | 0.05% | 68.16% |
| 289 | POLICE | 51 | 0.5 | 0.05% | 68.21% |
| 290 | PT:UP-LOC | 51 | 0.5 | 0.05% | 68.26% |
| 291 | NECESSARILY | 51 | 0.5 | 0.05% | 68.31% |
| 292 | AT ONCE2 | 50 | 0.5 | 0.05% | 68.36% |
| 293 | BECAUSE OF | 50 | 0.5 | 0.05% | 68.41% |
| 294 | DECIDE | 50 | 0.5 | 0.05% | 68.46% |
| 295 | ESCAPE | 49 | 0.5 | 0.05% | 68.51% |
| 296 | JUSTICE | 49 | 0.5 | 0.05% | 68.56% |
| 297 | RUN | 49 | 0.5 | 0.05% | 68.61% |
| 298 | READY | 49 | 0.5 | 0.05% | 68.66% |
| 299 | MESSAGING | 49 | 0.5 | 0.05% | 68.71% |
| 300 | PT:OTHER-LOC | 49 | 0.5 | 0.05% | 68.76% |
© 2021 Faculty of English, Adam Mickiewicz University, Poznań, Poland
Articles in the same Issue
- Table of contents
- Perceptual mapping of linguistic variation in Saudi Arabic dialects
- Some notes on central causal clauses in Venetian
- Between feature mapping and thematic prominence: Old english se-demonstratives and pronouns in discourse
- What the frequency list can teach us about Turkish sign language?
- Engagement markers in research project websites: Promoting interactivity and dialogicity
- A sociolinguistic study of address terms in a Nigerian university’s staff club
- Book review
Articles in the same Issue
- Table of contents
- Perceptual mapping of linguistic variation in Saudi Arabic dialects
- Some notes on central causal clauses in Venetian
- Between feature mapping and thematic prominence: Old english se-demonstratives and pronouns in discourse
- What the frequency list can teach us about Turkish sign language?
- Engagement markers in research project websites: Promoting interactivity and dialogicity
- A sociolinguistic study of address terms in a Nigerian university’s staff club
- Book review