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- Volume 24, Issue 1, 2019
International Journal of Corpus Linguistics - Volume 24, Issue 1, 2019
Volume 24, Issue 1, 2019
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Dimensions of variation across American television registers
Author(s): Tony Berber Sardinha and Marcia Veirano Pintopp.: 3–32 (30)More LessAbstractThe goal of this study is to identify the dimensions of variation across American television programs, following the multidimensional analysis (MD) framework introduced by Biber (1988). Although television is a major form of mass communication, there has been no previous large-scale MD study of television dialogue. A large corpus containing the key types of contemporary American television programs was collected, annotated with the Biber tagger, and subjected to multi-dimensional analysis, which indicated four factors of statistically correlated linguistic features. Each of these factors was interpreted communicatively to reveal the underlying dimensions of variation on American television, namely “Exposition and discussion vs. Simplified interaction” (Dimension 1), “Simulated conversation” (Dimension 2), “Recount” (Dimension 3) and “Engaging presentation” (Dimension 4). This article presents, illustrates, and discusses each of these dimensions, showing the macro linguistic patterns in use across hundreds of American television programs.
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Vocabulary sophistication in First-Year Composition assignments
Author(s): Philip Durrant, Joseph Moxley and Lee McCallumpp.: 33–66 (34)More LessAbstractRecently-developed tools which quickly and reliably quantify vocabulary use on a range of measures open up new possibilities for understanding the construct of vocabulary sophistication. To take this work forward, we need to understand how these different measures relate to each other and to human readers’ perceptions of texts. This study applied 356 quantitative measures of vocabulary use generated by an automated vocabulary analysis tool (Kyle & Crossley, 2015) to a large corpus of assignments written for First-Year Composition courses at a university in the United States. Results suggest that the majority of measures can be reduced to a much smaller set without substantial loss of information. However, distinctions need to be retained between measures based on content vs. function words and on different measures of collocational strength. Overall, correlations with grades are reliable but weak.
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The indicative vs. subjunctive alternation with expressions of possibility in Spanish
Author(s): Sandra C. Deshors and Mark Waltermirepp.: 67–97 (31)More LessAbstractThis study explores the indicative vs. subjunctive alternation in Spanish subordinate clauses following epistemic adverbials and expressions of possibility. Anchored in semantic-pragmatic and variationist theoretical frameworks, traditional research on mood alternation in Spanish remains largely experimental in nature. In contrast, we adopt a corpus-based multifactorial methodology to investigate 4,199 occurrences of fourteen expressions of possibility extracted from the Corpus del Español (e.g. caso de que, poder ser que, por si acaso, posiblemente, etc.) annotated contextually for structural, semantic and stylistic variables. Methodologically, we conduct an exploratory multiple correspondence analysis followed by a confirmatory binary logistic regression to examine whether/how the linguistic contexts affect mood variation. Overall, the results indicate that previously unexplored semantic factors (such as the inherent lexical aspect of verbs in subordinate clauses) significantly influence mood variation in Spanish. Ultimately, our results suggest that subjunctive uses are less uniform and more prone to internal variation than indicative uses.
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Do speech registers differ in the predictability of words?
Author(s): Martijn Bentum, Louis ten Bosch, Antal van den Bosch and Mirjam Ernestuspp.: 98–130 (33)More LessAbstractPrevious research has demonstrated that language use can vary depending on the context of situation. The present paper extends this finding by comparing word predictability differences between 14 speech registers ranging from highly informal conversations to read-aloud books. We trained 14 statistical language models to compute register-specific word predictability and trained a register classifier on the perplexity score vector of the language models. The classifier distinguishes perfectly between samples from all speech registers and this result generalizes to unseen materials. We show that differences in vocabulary and sentence length cannot explain the speech register classifier’s performance. The combined results show that speech registers differ in word predictability.
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Brezina, V. (2018). Statistics in Corpus Linguistics: A Practical Guide
Author(s): Ingo Kleiberpp.: 131–135 (5)More LessThis article reviews Statistics in Corpus Linguistics: A Practical Guide
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Rühlemann, C. (2018). Corpus Linguistics for Pragmatics: A Guide for Research
Author(s): Rachele De Felicepp.: 136–141 (6)More LessThis article reviews Corpus Linguistics for Pragmatics: A Guide for Research
Volumes & issues
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Volume 29 (2024)
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Volume 28 (2023)
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Volume 27 (2022)
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Volume 26 (2021)
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Volume 25 (2020)
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Volume 24 (2019)
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Volume 23 (2018)
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Volume 22 (2017)
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Volume 21 (2016)
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Volume 20 (2015)
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Volume 19 (2014)
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Volume 18 (2013)
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Volume 17 (2012)
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Volume 16 (2011)
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Volume 15 (2010)
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Volume 14 (2009)
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Volume 13 (2008)
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Volume 12 (2007)
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Volume 11 (2006)
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Volume 10 (2005)
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Volume 9 (2004)
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Volume 8 (2003)
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Volume 7 (2002)
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Volume 6 (2001)
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Volume 5 (2000)
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Volume 4 (1999)
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Volume 3 (1998)
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Volume 2 (1997)
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Volume 1 (1996)
Most Read This Month
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Comparing Corpora
Author(s): Adam Kilgarriff
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