Deep Language Statistics of Italian throughout Seven Centuries of Literature and Empirical Connections with Miller’s 7 ∓ 2 Law and Short-Term Memory — Oak Academic Publishing
Research ArticleOpen AccessGoogle Scholar indexed
Deep Language Statistics of Italian throughout Seven Centuries of Literature and Empirical Connections with Miller’s 7 ∓ 2 Law and Short-Term Memory
Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy
1 Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy
Statistics of languages are usually calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G — the semantic index , proportional to the number of characters per word, and the syntactic index G F , proportional to the reciprocal of the number of words per sentence — G F is dominant because G C is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y = mx , but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is that between the short - term memory capacity, described by Miller’s “7 ? 2 law” ( i.e. , the number of “chunks” that an average person can hold in the short - term memory ranges from 5 to 9), and the word interval , a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval spread s in the same range as Miller’s law, and the time interval is spread in the same range of short - term memory response times. The connection between the word interval (and time interval) and short - term memory appears, at least empirically, justified and natural, however , to be further investigated. Technical and scientific writings (papers, essays , etc.) ask more to their readers because words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as the classical Greek and Latin Literatures (or modern languages Literatures), could bring us an insight into the short - term memory required to their well-educated ancient readers.
Grzybeck, P. (2007) History and Methodology of Word Length Studies. In: Contributions to the Science of Text and Language, Springer, Dordrecht, 15-90. https://doi.org/10.1007/1-4020-4068-7_2
DuBay, W.H. (2004) The Principles of Readability. Impact Information, Costa Mesa.
DuBay, W.H. (2006) The Classic Readability Studies. Impact Information, Costa Mesa.
Anderson, P.V. (1991) Technical Writing: A Reader-Centered Approach. 2nd Edition, Harcourt Brace Jovanovich, Fort Worth.
Matricciani, E. (2007) La scrittura tecnico-scientifica. Casa Editrice Ambrosiana, Milano.
Saaty, T.L. and Ozdemir, M.S. (2003) Why the Magic Number Seven Plus or Minus Two. Mathematical and Computer Modelling, 38, 233-244. https://doi.org/10.1016/S0895-7177(03)90083-5
Zamanian, M. and Heydari, P. (2012) Readability of Texts: State of the Art. Theory and Practice in Language Studies, 2, 43-53. https://doi.org/10.4304/tpls.2.1.43-53
Collins-Thompson, K. (2014) Computational Assessment of Text Readability: A Survey of Past, in Present and Future Research, Recent Advances in Automatic Readability Assessment and Text Simplification, ITL. International Journal of Applied Linguistics, 165, 97-135. https://doi.org/10.1075/itl.165.2.01col
Baddeley, A.D., Thomson, N. and Buchanan, M. (1975) Word Length and the Structure of Short-Term Memory. Journal of Verbal Learning and Verbal Behavior, 14, 575-589. https://doi.org/10.1016/S0022-5371(75)80045-4
Barrouillest, P. and Camos, V. (2012) As Time Goes By: Temporal Constraints in Working Memory. Current Directions in Psychological Science, 21, 413-419. https://doi.org/10.1177/0963721412459513
Jones, G. and Macken, B. (2015) Questioning Short-Term Memory and Its Measurements: Why Digit Span Measures Long-Term Associative Learning. Cognition, 144, 1-13. https://doi.org/10.1016/j.cognition.2015.07.009
Chekaf, M., Cowan, N. and Mathy, F. (2016) Chunk Formation in Immediate Memory and How It Relates to Data Compression. Cognition, 155, 96-107. https://doi.org/10.1016/j.cognition.2016.05.024
Bailin, A. and Graftstein, A. (2001) The Linguistic Assumptions Underlying Readability Formulae: A Critique. Language & Communication, 21, 285-301. https://doi.org/10.1016/S0271-5309(01)00005-2
Word Interval
Benjamin, R.G. (2012) Reconstructing Readability: Recent Developments and Recommendations in the Analysis of Text Difficulty. Educational Psychology Review, 24, 63-88. https://doi.org/10.1007/s10648-011-9181-8
Vajjala, S., Meurers, D., Eitel, A. and Scheiter, K. (2016) Towards Grounding Computational Linguistic Approaches to Readability: Modelling Reader-Text Interaction for Easy and Difficult Texts. Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity, Osaka, 11-17 December 2016, 38-48.
Dell’Orletta, F., Montemagni, S. and Venturi, G. (2011) Read-It: Assessing Readability of Italian Texts with a View to Text Simplification. Proceedings of the 2nd Workshop on Speech and Language Processing for Assistive Technologies, Edinburgh, 30 July 2011, 73-83.
De Mauro, T. (1980) Guida all’uso delle parole. Editori Riuniti, Roma.
Atvars, A. (2016) Eye Movement Analyses for Obtaining Readability Formula for Latvian Texts for Primary School. Procedia Computer Science, 104, 477-484. https://doi.org/10.1016/j.procs.2017.01.162
Conway, A.R.A., Cowan, N., Bunting, M.F., Therriaulta, D.J. and Minkoff, S.R.B. (2002) A Latent Variable Analysis of Working Memory Capacity, Short-Term Memory Capacity, Processing Speed, and General Fluid Intelligence. Intelligence, 30, 163-183. https://doi.org/10.1016/S0160-2896(01)00096-4
Miller, G.A. (1955) The Magical Number Seven, plus or Minus Two: Some Limits on Our Capacity for Processing Information. Psychological Review, 101, 343-352. https://doi.org/10.1037/0033-295X.101.2.343
Grondin, S. (2000) A Temporal Account of the Limited Processing Capacity. Behavioral and Brain Sciences, 24, 122-123. https://doi.org/10.1017/S0140525X01303928
Muter, P. (2000) The Nature of Forgetting from Short-Term Memory. Behavioral and Brain Sciences, 24, 134. https://doi.org/10.1017/S0140525X01423922
Matricciani, E. and De Caro, L. (2019) A Deep-Language Mathematical Analysis of Gospels, Acts and Revelation. Religions, 10, 257. https://doi.org/10.3390/rel10040257
Lucisano, P. and Piemontese, M.E. (1988) GULPEASE: Una formula per la predizione della difficoltà dei testi in lingua italiana. Scuola e città, 3, 110-124.
Martin, L. and Gottron, T. (2012) Readability and the Web. Future Internet, 4, 238-252. https://doi.org/10.3390/fi4010238
Parkes, M.B. (2016) Pause and Effect. An Introduction to the History of Punctuation in the West. Routledge, Abingdon-on-Thames, 343 p. https://doi.org/10.4324/9781315247243
Maraschio, N. (1993) Grafia e ortografia: Evoluzione e codificazione. In: L. Serianni, & P. Trifone (Eds.), Storia della lingua italiana: I luoghi della codificazione, Einaudi, Torino, 139-227.
Mortara Garavelli, B. (2003) Prontuario di punteggiatura, Editori Laterza.
Serianni, L. (2001) Sul punto e virgola nell’italiano contemporaneo. Studi Linguistici italiani, 27, 248-255.
Gómez-Adorno, E., Sidorov, G., Pinto, D., Vilarino, D. and Gelbukh, A. (2016) Automatic Authorship Detection Using Textual Patterns Extracted from Integrated Syntactic Graphs. Sensors, 16, 1374. https://doi.org/10.3390/s16091374
Stamatatos, E. (2009) A Survey of Modern Authorship Attribution Methods. Journal of the American Society for Information Science and Technology, 60, 538-556. https://doi.org/10.1002/asi.21001
Cowan, N. (2000) The Magical Number 4 in Short-Term Memory: A Reconsideration of Mental Storage Capacity. Behavioral and Brain Sciences, 24, 87-114. https://doi.org/10.1017/S0140525X01003922
Bachelder, B.-L. (2001) The Magical Number 4 = 7: Span Theory on Capacity Limitations. Behavioral and Brain Sciences, 24, 116-117. https://doi.org/10.1017/S0140525X01243921
Chen, Z. and Cowan, N. (2005) Chunk Limits and Length Limits in Immediate Recall: A Reconciliation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 3, 1235-1249. https://doi.org/10.1037/0278-7393.31.6.1235
Mathy, F. and Feldman, J. (2012) What’s Magic about Magic Numbers? Chunking and Data Compression in Short-Term Memory. Cognition, 122, 346-362. https://doi.org/10.1016/j.cognition.2011.11.003
Gignac, G.E. (2015) The Magical Numbers 7 and 4 Are Resistant to the Flynn Effect: No Evidence for Increases in Forward or Backward Recall across 85 Years of Data. Intelligence, 48, 85-95. https://doi.org/10.1016/j.intell.2014.11.001
Papoulis, A. (1990) Probability & Statistics. Prentice Hall, Upper Saddle River.
Bury, K.V. (1975) Statistical Models in Applied Science. John Wiley, Hoboken.
Jarvella, R.J. (1971) Syntactic Processing of Connected Speech. Journal of Verbal Learning and Verbal Behavior, 10, 409-416. https://doi.org/10.1016/S0022-5371(71)80040-3
Trauzettel-Klosinski, S. and Dietz, K. (2012) Standardized Assessment of Reading Performance: The New International Reading Speed Texts IReST. Investigative Ophthalmology & Visual Science, 53, 5452-5461. https://doi.org/10.1167/iovs.11-8284
Mandler, G. and Shebo, B.J. (1982) Subitizing: An Analysis of Its Component Processes. Journal of Experimental Psychology: General, 111, 1-22. https://doi.org/10.1037//0096-3445.111.1.1
Pothos, E.M. and Joula, P. (2000) Linguistic Structure and Short-Term Memory. Behavioral and Brain Sciences, 24, 138-139. https://doi.org/10.1017/S0140525X01463928