Modeling Language Characteristics of Leaders in Authoritarian Regimes over Decades

The present research investigated the linguistic patterns in the discourse of three prominent autocratic political leaders whose reigns lasted for multiple decades. The texts of Fidel Castro, Zedong Mao, and Hosni Mubarak were analyzed using computational linguistic methodologies and nonlinear modeling techniques to explore the temporal trajectory of formality over time. Specifically, this metric of formality increases with abstractness of words, syntactic complexity, cohesion (referential and deep), and the informational genre (as opposed to narrative). At the other end of the continuum, informal discourse tends to have concrete words, simple syntax, low cohesion and high narrativity. The findings are aligned with theoretically grounded hypotheses of aging and persuasion in hopes of identifying which most appropriately explains the formality of leaders’ political texts

Linguistic Signatures of Cognitive Processes during Writing

The relationship between working memory capacity andwriting ability was examined via a linguistic analysis ofstudent essays. Undergraduate students (n = 108) wrotetimed, prompt-based essays and completed a battery ofcognitive assessments. The surface- and discourse-levellinguistic features of students’ essays were then analyzedusing natural language processing tools. The results indicatedthat WM capacity was related to surface-level, but notdiscourse-level features of student essays. Additionally, theresults suggest that these relationships were attenuated forstudents with high inferencing skills, as opposed to those withlower inferencing skill

The Effects of Text Complexity on Online Review Helpfulness

This research reported in this paper extends the literature on the helpfulness of online reviews. Previous research has assessed online reviews using standard unidimensional readability algorithms. This research extends previous work by investigating a multidimensional framework, and associated measures, of text complexity and its impact on the helpfulness of online reviews. Results show that as the amount of passive voice and negation in online reviews increase, the helpfulness of said review decreases. Other significant predictors of review helpfulness include word meaningfulness, lexical diversity, and the number of modifiers per noun phrase

The Time-Course of Lexical and Structural Processes in Sentence Comprehension

Online sentence comprehension involves multiple types of cognitive processes: lexical processes such as lexical access, which call on the user's knowledge of the meaning of words in the language, and structural processes such as the integration of incoming words into an emerging representation. In this article, we investigate the temporal dynamics of lexical access and syntactic integration. Unlike much previous work that has relied on temporary ambiguity to investigate this question, we manipulate the frequency of the verb in unambiguous structures involving a well-studied syntactic complexity manipulation (subject- vs. object-extracted clefts). The results demonstrate that for high-frequency verbs, the difficulty of reading a more structurally complex object-extracted cleft structure relative to a less structurally complex subject-extracted cleft structure is largely experienced in the cleft region, whereas for low-frequency verbs this difficulty is largely experienced in the postcleft region. We interpret these results as evidence that some stages of structural processing follow lexical processing. Furthermore, we find evidence that structural processing may be delayed if lexical processing is costly, and that the delay is proportional to the difficulty of the lexical process. Implications of these results for contemporary accounts of sentence comprehension are discussed

Examining the Role of Linguistic Flexibility in the Text Production Process

abstract: A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the writing literature. Research suggests that higher quality writing is typically associated with decreased levels of text narrativity and readability. Although narrative elements may sometimes be associated with high-quality writing, the majority of research suggests that higher quality writing is associated with decreased levels of text narrativity, and measures of readability in general. One potential explanation for this conflicting evidence lies in the situational influence of text elements on writing quality. In other words, it is possible that the frequency of specific linguistic or rhetorical text elements alone is not consistently indicative of essay quality. Rather, these effects may be largely driven by individual differences in students' ability to leverage the benefits of these elements in appropriate contexts. This dissertation presents the hypothesis that writing proficiency is associated with an individual's flexible use of text properties, rather than simply the consistent use of a particular set of properties. Across three experiments, this dissertation relies on a combination of natural language processing and dynamic methodologies to examine the role of linguistic flexibility in the text production process. Overall, the studies included in this dissertation provide important insights into the role of flexibility in writing skill and develop a strong foundation on which to conduct future research and educational interventions.Dissertation/ThesisDoctoral Dissertation Psychology 201

A Study on Text Cohesion in Senior High Students’ Continuation Writing Based on Coh-Metrix

Continuation writing is a new type of writing task introduced in the Chinese college entrance examination reform. Text cohesion is essential for a well-written continuation. Cohesion in a text can be explicit, involving language-level textual cohesion, or implicit, involving semantic-level meaning continuity. This study uses the text analysis software Coh-Metrix to analyze the cohesion in high school students’ English continuation writing. It explores the features of coherence in these writings from both the explicit language usage and the implicit semantic continuity, and the differences between the high-scoring group and the low-scoring group, aiming to provide effective teaching suggestions and references for English teachers

A Lightweight Regression Method to Infer Psycholinguistic Properties for Brazilian Portuguese

Psycholinguistic properties of words have been used in various approaches to Natural Language Processing tasks, such as text simplification and readability assessment. Most of these properties are subjective, involving costly and time-consuming surveys to be gathered. Recent approaches use the limited datasets of psycholinguistic properties to extend them automatically to large lexicons. However, some of the resources used by such approaches are not available to most languages. This study presents a method to infer psycholinguistic properties for Brazilian Portuguese (BP) using regressors built with a light set of features usually available for less resourced languages: word length, frequency lists, lexical databases composed of school dictionaries and word embedding models. The correlations between the properties inferred are close to those obtained by related works. The resulting resource contains 26,874 words in BP annotated with concreteness, age of acquisition, imageability and subjective frequency.Comment: Paper accepted for TSD201

Reflecting Comprehension through French Textual Complexity Factors

International audienceResearch efforts in terms of automatic textual complexity analysis are mainly focused on English vocabulary and few adaptations exist for other languages. Starting from a solid base in terms of discourse analysis and existing textual complexity assessment model for English, we introduce a French model trained on 200 documents extracted from school manuals pre-classified into five complexity classes. The underlying textual complexity metrics include surface, syntactic, morphological, semantic and discourse specific factors that are afterwards combined through the use of Support Vector Machines. In the end, each factor is correlated to pupil comprehension metrics scores, spanning throughout multiple classes, therefore creating a clearer perspective in terms of measurements impacting the perceived difficulty of a given text. In addition to purely quantitative surface factors, specific parts of speech and cohesion have proven to be reliable predictors of learners' comprehension level, creating nevertheless a strong background for building dependable French textual complexity models