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This paper presents a combination of R packages-user contributed toolkits written in a common core programming language-to facilitate the humanistic investigation of digitised, text-based corpora.Our survey of text analysis packages includes those of our own creation (cleanNLP and fasttextM) as well as packages built by other research groups (stringi, readtext, hyphenatr, quanteda, and hunspell). By operating on generic object types, these packages unite research innovations in corpus linguistics, natural language processing, machine learning, statistics, and digital humanities. We begin by extrapolating on the theoretical benefits of R as an elaborate gluing language for bringing together several areas of expertise and compare it to linguistic concordancers and other tool-based approaches to text analysis in the digital humanities. We then showcase the practical benefits of an ecosystem by illustrating how R packages have been integrated into a digital humanities project. Throughout, the focus is on moving beyond the bag-of-words, lexical frequency model by incorporating linguistically-driven analyses in research.
This article presents a corpus-based evaluation of 13 lexical diversity metrics as measures of longitudinal progression in written productions of learners of French as third language (L3). Our case study (24 learners, 3 productions per learner in the course of 3 months) deals with a semi-longitudinal corpus, where each of the productions is supposed to be more complex than the previous one. Random forests (Breiman, 2001; Hothorn et al., 2019) are used in order to see whether lexical diversity metric scores capture enough vocabulary diversity progression to predict the production wave. We report that lexical diversity metrics capture lexical progression through the three productions of each student. In particular, two metrics appear to be the most informative for lexical progression: Herdan’s C and Yule’s K.
It is well-known that individuals with aphasia (IWA) have difficulties understanding sentences that involve non-adjacent dependencies, such as object relative clauses or passives (Caplan, Baker, & Dehaut, 1985; Caramazza & Zurif, 1976). A large body of research supports the view that IWA’s grammatical system is intact, and that comprehension difficulties in aphasia are caused by a processing deficit, such as a delay in lexical access and/or in syntactic structure building (e.g., Burkhardt, Piñango, & Wong, 2003; Caplan, Michaud, & Hufford, 2015; Caplan, Waters, DeDe, Michaud, & Reddy, 2007; Ferrill, Love, Walenski, & Shapiro, 2012; Hanne, Burchert, De Bleser, & Vasishth, 2015; Love, Swinney, Walenski, & Zurif, 2008). The main goal of this dissertation is to computationally investigate the processing sources of comprehension impairments in sentence processing in aphasia.
In this work, prominent theories of processing deficits coming from the aphasia literature are implemented within two cognitive models of sentence processing –the activation-based model (Lewis & Vasishth, 2005) and the direct-access model (McEl- ree, 2000)–. These models are two different expressions of the cue-based retrieval theory (Lewis, Vasishth, & Van Dyke, 2006), which posits that sentence processing is the result of a series of iterative retrievals from memory. These two models have been widely used to account for sentence processing in unimpaired populations in multiple languages and linguistic constructions, sometimes interchangeably (Parker, Shvarts- man, & Van Dyke, 2017). However, Nicenboim and Vasishth (2018) showed that when both models are implemented in the same framework and fitted to the same data, the models yield different results, because the models assume different data- generating processes. Specifically, the models hold different assumptions regarding the retrieval latencies. The second goal of this dissertation is to compare these two models of cue-based retrieval, using data from individuals with aphasia and control participants. We seek to answer the following question: Which retrieval mechanism is more likely to mediate sentence comprehension?
We model 4 subsets of existing data: Relative clauses in English and German; and control structures and pronoun resolution in German. The online data come from either self-paced listening experiments, or visual-world eye-tracking experiments. The offline data come from a complementary sentence-picture matching task performed at the end of the trial in both types of experiments. The two competing models of retrieval are implemented in the Bayesian framework, following Nicenboim and Vasishth (2018). In addition, we present a modified version of the direct-acess model that – we argue – is more suitable for individuals with aphasia.
This dissertation presents a systematic approach to implement and test verbally- stated theories of comprehension deficits in aphasia within cognitive models of sen- tence processing. The conclusions drawn from this work are that (a) the original direct-access model (as implemented here) cannot account for the full pattern of data from individuals with aphasia because it cannot account for slow misinterpretations; and (b) an activation-based model of retrieval can account for sentence comprehension deficits in individuals with aphasia by assuming a delay in syntactic structure building, and noise in the processing system. The overall pattern of results support an activation-based mechanism of memory retrieval, in which a combination of processing deficits, namely slow syntax and intermittent deficiencies, cause comprehension difficulties in individuals with aphasia.
An important aspect of aphasia is the observation of behavioral variability between and within individual participants. Our study addresses variability in sentence comprehension in German, by testing 21 individuals with aphasia and a control group and involving (a) several constructions (declarative sentences, relative clauses and control structures with an overt pronoun or PRO), (b) three response tasks (object manipulation, sentence-picture matching with/without self-paced listening), and (c) two test phases (to investigate test-retest performance). With this systematic, large-scale study we gained insights into variability in sentence comprehension. We found that the size of syntactic effects varied both in aphasia and in control participants. Whereas variability in control participants led to systematic changes, variability in individuals with aphasia was unsystematic across test phases or response tasks. The persistent occurrence of canonicity and interference effects across response tasks and test phases, however, shows that the performance is systematically influenced by syntactic complexity.