Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
A Novel Interaction Protocol of a Multiagent System for the Study of Alternative Decisions Read chapter Read first chapter

2016 | OriginalPaper | Chapter

What Makes Your Writing Style Unique? Significant Differences Between Two Famous Romanian Orators

Authors : Mihai Dascalu, Daniela Gîfu, Stefan Trausan-Matu

Published in: Computational Collective Intelligence

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This paper introduces a novel, in-depth approach of analyzing the differences in writing style between two famous Romanian orators, based on automated textual complexity indices for Romanian language. The considered authors are: (a) Mihai Eminescu, Romania’s national poet and a remarkable journalist of his time, and (b) Ion C. Brătianu, one of the most important Romanian politicians from the middle of the 18th century. Both orators have a common journalistic interest consisting in their desire to spread the word about political issues in Romania via the printing press, the most important public voice at that time. In addition, both authors exhibit writing style particularities, and our aim is to explore these differences through our ReaderBench framework that computes a wide range of lexical and semantic textual complexity indices for Romanian and other languages. The used corpus contains two collections of speeches for each orator that cover the period 1857–1880. The results of this study highlight the lexical and cohesive textual complexity indices that reflect very well the differences in writing style, measures relying on Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) semantic models.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter WSD-TIC: Word Sense Disambiguation Using Taxonomic Information Content
next chapter A Novel Approach to Identify Factor Posing Pronunciation Disorders
Literature
1.
de Saussure, F.: Cours de Linguistique Générale. Payot, Paris (1999)
2.
Bo, L., Gaussier, E., Morin, E., Hazem, A.: Degré de comparabilité, extraction lexicale bilingue et recherche d’information interlingue. In: Conf´erence sur le Traitement Automatique des Langues Naturelles, vol. 1, pp. 211–222. LIRMM Montpellier, Montpellier (2011)
3.
Morin, E., Daille, B.: Comparabilité de corpus et fouille terminologique multilingue. Traitement Automatique des Langues 47(1), 113–136 (2006)
4.
Gîfu, D.: Contrastive diachronic study on romanian language. In: FOI 2015, pp. 296–310. Institute of Mathematics and Computer Science, Academy of Sciences of Moldova (2015)
5.
Aijmer, K., Altenberg, B., Johansson, M.: Languages in contrast: papers from a symposium on text-based cross-linguistic studies, Lund 4–5 March 1994, vol. 88. Lund studies in English (1996)
6.
Vianu, T.: Arta prozatorilor români. Ed. Contemporană, Bucharest (1941)
7.
Coteanu, I.: Stilistica Funcțională a Limbii Române, vol. 81. Editura Academiei, Bucharest (1993)
8.
Ibrăileanu, G.: Spiritul Critic în Cultura Românească. Tipografia Moldova, Iaşi (2001)
9.
Brătianu, I.C.: Memoire sur l’Empire d’Autriche dans la question d’Orient, Paris, France (1855)
10.
Brătianu, I.C.: Memoire sur la situation de la Moldo–Valachie depuis la Traite de Paris, Paris, France (1857)
11.
Dascalu, M.: Analyzing Discourse and Text Complexity for Learning and Collaborating. SCI, vol. 534. Springer, Cham (2014)
12.
Dascalu, M., Gifu, D.: Evaluating the complexity of online Romanian press. In: 11th International Conference “Linguistic Resources and Tools for Processing the Romanian Language”, Iasi, Romania, pp. 149–162 (2015)
13.
Dascalu, M., Dessus, P., Bianco, M., Trausan-Matu, S., Nardy, A.: Mining texts, learner productions and strategies with ReaderBench. In: Peña-Ayala, A. (ed.) Educational Data Mining. SCI, vol. 524, pp. 335–377. Springer, Cham (2014)CrossRef
14.
Dascalu, M., Stavarache, L.L., Dessus, P., Trausan-Matu, S., McNamara, D.S., Bianco, M.: ReaderBench: an integrated cohesion-centered framework. In: Conole, G., Klobucar, T., Rensing, C., Konert, J., Lavoué, E. (eds.) EC-TEL 2015. LNCS, vol. 9307, pp. 505–508. Springer, Heidelberg (2015). doi:10.​1007/​978-3-319-24258-3_​47
15.
National Governors Association Center for Best Practices & Council of Chief State School Officers: Common Core State Standards. Authors, Washington D.C. (2010)
16.
Eggins, S., Martin, J.R.: Genres and register of discourse. In: van Dijk, T.A. (ed.) Discourse as Structure and Process (Discourse Studies – A Multidisciplinary Introduction), vol. 1, pp. 231–232. Sage Publications, London (1997)
17.
Biber, D.: A textual comparison of British and American Writing. Am. Speech 62, 99–119 (1987)CrossRef
18.
Rosetti, A., Cazacu, B., Onu, L.: Istoria limbii române literare. Editura Minerva, Bucureşti (1971)
19.
Iordan, I.: Stilistica Limbii Române. Editura Ştiințifică, Bucureşti (1975)
20.
Sala, M.: De la latină la română. Limba română, vol. 1. Editura Univers Enciclopedic & Academia Română, Bucureşti (1998)
21.
Guţu-Romalo, V.: Aspecte ale evoluţiei limbii române, Vol. Repere. Editura Humanitas Educaţional, Bucureşti (2005)
22.
Slotnick, H.: Toward a theory of computer essay grading. J. Educ. Meas. 9(4), 253–263 (1972)CrossRef
23.
Wresch, W.: The imminence of grading essays by computer—25 years later. Comput. Compos. 10(2), 45–58 (1993)CrossRef
24.
Nelson, J., Perfetti, C., Liben, D., Liben, M.: Measures of text difficulty: Testing their predictive value for grade levels and student performance. Council of Chief State School Officers, Washington, DC (2012)
25.
Shannon, C.E.: Prediction and entropy of printed English. Bell Syst. Tech. J. 30, 50–64 (1951)CrossRefMATH
26.
Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J., 27, 379–423 & 623–656 (1948)
27.
Gervasi, V., Ambriola, V.: Quantitative assessment of textual complexity. In: Barbaresi, M.L. (ed.) Complexity in Language and Text, pp. 197–228. Plus, Pisa (2002)
28.
McNamara, D.S., Graesser, A.C., Louwerse, M.M.: Sources of text difficulty: Across the ages and genres. In: Sabatini, J.P., Albro, E., O’Reilly, T. (eds.) Measuring up: Advances in how we assess reading ability, pp. 89–116. R&L Education, Lanham (2012)
29.
van Dijk, T.A., Kintsch, W.: Strategies of Discourse Comprehension. Academic Press, New York (1983)
30.
Crossley, S.A., Dascalu, M., Trausan-Matu, S., Allen, L., McNamara, D.S.: Document Cohesion Flow: Striving towards Coherence. In: 38th Annual Meeting of the Cognitive Science Society. Cognitive Science Society, Philadelphia (in press)
31.
Dascalu, M., Trausan-Matu, S., McNamara, D.S., Dessus, P.: ReaderBench – automated evaluation of collaboration based on cohesion and dialogism. Int. J. Comput.-Support. Collaborative Learn. 10(4), 395–423 (2015)CrossRef
32.
Dascalu, M., Dessus, P., Trausan-Matu, Ş., Bianco, M., Nardy, A.: ReaderBench, an environment for analyzing text complexity and reading strategies. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds.) AIED 2013. LNCS, vol. 7926, pp. 379–388. Springer, Heidelberg (2013)CrossRef
33.
Trausan-Matu, S., Dascalu, M., Dessus, P.: Textual complexity and discourse structure in computer-supported collaborative learning. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds.) ITS 2012. LNCS, vol. 7315, pp. 352–357. Springer, Heidelberg (2012)CrossRef
34.
Foltz, P.W., Kintsch, W., Landauer, T.K.: An analysis of textual coherence using latent semantic indexing. In: 3rd Annual Conference of the Society for Text and Discourse, Boulder, CO (1993)
35.
Landauer, T.K., Dumais, S.T.: A solution to Plato’s problem: the Latent semantic analysis theory of acquisition, induction and representation of knowledge. Psychol. Rev. 104(2), 211–240 (1997)CrossRef
36.
Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)MATH
37.
Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3(4–5), 993–1022 (2003)MATH
38.
Blei, D.M., Lafferty, J.: Topic models. In: Srivastava, A., Sahami, M. (eds.) Text Mining: Classification, Clustering, and Applications, pp. 71–93. Chapman & Hall/CRC, London (2009)
39.
Golub, G.H., Kahan, W.: Calculating the singular values and pseudo-inverse of a matrix. J. Soc. Ind. Appl. Math.: Ser. B, Numer. Anal. 2(2), 205–224 (1965)MathSciNetCrossRefMATH
40.
Kotz, S., Balakrishnan, N., Johnson, N.L.: Dirichlet and Inverted Dirichlet Distributions. Continuous Multivariate Distributions, vol. 1, Models and Applications, pp. 485–527. Wiley, New York (2000)
41.
Dascalu, M., Trausan-Matu, S., Dessus, P., McNamara, D.S.: Discourse cohesion: a signature of collaboration. In: 5th International Learning Analytics & Knowledge Conference (LAK 2015), pp. 350–354. ACM, Poughkeepsie (2015)
42.
Tufiș, D., Barbu Mititelu, V., Bozianu, L., Mihăilă, C.: Romanian wordnet: new developments and applications. In: 3rd Global Wordnet Conference 2006 (GWC 2006), Jeju Island, Korea, pp. 337–344 (2006)
43.
Stevens, J.P.: Applied multivariate statistics for the social sciences. Lawrence Erblaum, Mahwah (2002)MATH
44.
Garson, G.D.: Multivariate GLM, MANOVA, and MANCOVA. Statistical Associates Publishing, Asheboro (2015)
Metadata
Title
What Makes Your Writing Style Unique? Significant Differences Between Two Famous Romanian Orators
Authors
Mihai Dascalu
Daniela Gîfu
Stefan Trausan-Matu
Copyright Year
2016
Book
Computational Collective Intelligence

Print ISBN: 978-3-319-45242-5

Electronic ISBN: 978-3-319-45243-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-45243-2_13

Premium Partner

    Image Credits