Syntactic Complexity Analyzer Research Articles

L2 English speaking syntactic complexity: Data preprocessing issues, reliability of automated analysis, and the effects of proficiency, L1 background, and topic

AbstractThe effects of learner‐ and task‐related variables on second language (L2) writing syntactic complexity (SC) have been extensively investigated. However, previous research has rarely assessed the reliability of computational tools for analyzing the SC of L2 spoken production, and we know less about the effects of such variables on L2 speaking SC. Using data from the International Corpus Network of Asian Learners of English, this study explores data preprocessing issues for preparing L2 English speech samples for automated SC analysis, evaluates the reliability of L2 Syntactic Complexity Analyzer on preprocessed L2 English speech samples, and examines the effects of proficiency, first language (L1) background, and topic on L2 speaking SC. Our manual analysis of 30 random speech samples identified several issues that can be addressed through preprocessing to improve the accuracy of automated SC analysis. Results from multiple linear mixed‐effects models revealed significant effects of proficiency, L1 background, and topic on the mean length of clause, the number of complex AS‐units per AS‐unit, and the number of dependent clauses and complex nominals per clause in L2 learners’ spoken production. Our findings have useful implications for L2 speaking pedagogy and assessment as well as future L2 speaking SC research.

Korean Syntactic Complexity Analyzer (KOSCA): An NLP application for the analysis of syntactic complexity in second language production

Given the lack of computational tools available for assessing second language (L2) production in Korean, this study introduces a novel automated tool called the Korean Syntactic Complexity Analyzer (KOSCA) for measuring syntactic complexity in L2 Korean production. As an open-source graphic user interface (GUI) developed in Python, KOSCA provides seven indices of syntactic complexity, including traditional and Korean-specific ones. Its validity was tested by investigating whether the syntactic complexity indices measured by it in L2 written and spoken production could explain the variability of L2 Korean learners’ proficiency. The results of mixed-effects regression analyses showed that all seven indices significantly accounted for learner proficiency in Korean. Subsequent stepwise multiple regression analyses revealed that the syntactic complexity indices explained 56.0% of the total variance in proficiency for the written data and 54.4% for the spoken data. These findings underscore the validity of the syntactic complexity indices measured by KOSCA as reliable indicators of L2 Korean proficiency, which can serve as a valuable resource for researchers and educators in the field of L2 Korean learning and assessment.

Modelling the use of the tool for the automatic analysis of syntactic sophistication and complexity (TAASSC)

This methods tutorial introduces the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity (TAASSC), a linguistic analysis tool developed by Kyle (2016). In the first part, the tutorial offers an accessible introduction to the key concepts and considerations for using the syntactic complexity and sophistication measures provided by TAASSC. It also overviews the incorporation of new lexico-grammatical features in more recent versions of TAASSC and compares the new versions with earlier versions. The second part of the tutorial guides users through the tool's application by demonstrating a case study of applying TAASSC to a linguistic analysis. It details the process of utilising TAASSC to obtain initial index profiles and conducting mixed-effects modelling using R. The focus is on analysing one aspect of the phrasal complexity development in British school children's writing across academic years, employing mixed-effects models to account for complex data structures and observation interdependence. This tutorial equips researchers with the knowledge to effectively employ TAASSC in linguistic analysis and showcases its utility in exploring syntactic complexity development.

A Comparative Analysis of Syntactic Complexity in Applied Linguistics Abstracts Written by Chinese Novice Writers and Native English Advanced Writers

A Comparative Analysis of Syntactic Complexity in Applied Linguistics Abstracts Written by Chinese Novice Writers and Native English Advanced Writers

A Comparative Analysis of Syntactic Complexity between Scholars and AI-based Machine Translation Systems

A Comparative Analysis of Syntactic Complexity between Scholars and AI-based Machine Translation Systems

It’s complicated: The relationship between lexis, syntax and proficiency

This paper explores the relationship between lexical and syntactic complexity measures and proficiency in L2 English argumentative essays written by L1 Czech high school students. Syntactic complexity is generally understood as referring to the “range and sophistication” (Ortega 2015) of grammatical constructions, whereas lexical complexity can refer to the range and frequency of the words used. The research used 100 essays written by final year high school students. Lexical complexity was analysed using the Lexical Complexity Analyzer (Ai & Lu 2010, Lu 2012), syntactic complexity using the L2 Syntactic Complexity Analyzer (Lu 2010, 2014) and Biber et al.’s (2011) hypothesised developmental stages for complexity framework. Despite a large number of measurements failing to produce any significant patterns, positive correlations were found between lexical diversity measures and vocabulary scores. Similarly, Mean Length of Clause (MLC) and Complex nominals per clause (CN/C) showed weak positive associations with grammar scores, as did Stage 5 of the developmental stages. The findings provide an insight into the kinds of complexity features that can be given more focus during instruction and underscore the potential of these measures as determinants of proficiency.

The Interplay of Linguistic Complexity Measuresand Their Relation tothe Qualityof L2 Argumentative Writing

Previous research revealed that syntactic and lexical complexity is crucial in predicting writing quality. However, measuring these features is difficult because they often interact in unpredictable ways. To address this challenge, measurement practices need to capture a more holistic view. This study aims to explore the integration of the complexity metrics and examines how they relate to L2 writing. A sample of 199 argumentative essays from an in-house English proficiency test was scrutinized using the Syntactic Complexity Analyzer and the Lexical Complexity Analyzer. Factor analysis and Pearson correlation were used for data analysis. The findings indicated that, syntactically, a higher frequency and richness of coordinate phrases were associated with superior L2 writing quality (r=.27, p<.01). Lexically, verb variation (r=.186), transformations of the number of different words measures (r=.241) and noun & mod variation (r=.233) were found to be valid indicators of L2 writing quality. However, different from previous research on narrative writing, verb sophistication is found to have no significant correlation with argumentative writing scores. It indicates that the genre of L2 production is a variable that may affect the validity of verb sophistication as a descriptor of L2 performance.

Retracted: Analysis of Syntactic Complexity and Semantic Coherence of Academic English Writing Based on Particle Swarm Optimization

Retracted: Analysis of Syntactic Complexity and Semantic Coherence of Academic English Writing Based on Particle Swarm Optimization

Identifying Stylometric Characteristics of Domain Specific Texts Using Classification Algorithms: A Study of Library Science Articles published in 2020

Academic writing has played an essential role in communicating the cognitive aspects of the human mind. Natural Language Processing (NLP) tools enable us to examine linguistic knowledge. However, writing patterns and applicable linguistic characteristics differ geographically. The study's primary purpose is to understand the global writing pattern and linguistic diversities of research articles in the LIS domain. The corpus was identified from four SCOPUS-enrolled open-access libraries and information science journals. The journals published in India and outside India were selected for the study in 2020. The syntactic complexity in 147 text documents was measured using the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity (TASSAC). The corpus was further examined using the Structural Equation Model (SEM) to determine the causal relationship among independent variables such as syntax features and readability scores. The results depict the differences in the patterning of syntactic features at both the global and national levels. Furthermore, the study allows us to see how linguistic diversity is underplayed in research writings and helps to understand writing patterns through cross-country comparisons. Furthermore, the paper employs model-based reasoning to identify global and national latent variables.

Verb argument construction complexity indices and L2 written production: effects of task complexity and task repetition

ABSTRACT This study examines the extent to which verb argument construction (VAC) based indices of syntactic complexity could predict four different writing task conditions: a simple task with no repetition (S + NR), a simple task with repetition (S + R), a complex task with no repetition (C + NR), and a complex task with repetition (C + R). Ninety-six high-intermediate second language (L2) learners of English performed two argumentative writing tasks and repeated them at one-week intervals, with the order of the tasks counterbalanced. The 384 essays collected at four different time points were analyzed in terms of VAC sophistication measures using the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity (Kyle 2016). Results indicated that S + R as well as C + NR and C + R conditions led to more lower-frequency VAC-verb combined structures used in the essays. Further analyses revealed a significant average association strength between verbs and VACs for the C + R group, showing the superiority of this condition over the others in developing syntactically complex argumentative essays. The implications for L2 writing pedagogy and assessment will be discussed.

Effects of teacher, automated, and combined feedback on syntactic complexity in EFL students’ writing

Although studies on written feedback have confirmed the effectiveness of multiple sources of feedback in promoting learners’ accuracy, much remains to be discovered about its impact on other aspects of language development. Concerns were raised with regard to the possible unfavourable impact of feedback on the complexity of students’ writing which resulted from their attention to producing accurate texts. In response to this need for research, the study investigated the effects of teacher, automated, and combined feedback on students’ syntactic complexity over a 13-week semester. Our data collection included 270 students’ texts including their drafts and revised texts and pre-and post-test writing. Essays were analysed using the web-based interface of the L2 Syntactic Complexity Analyzer. Regardless of feedback from multiple sources, paired sample t-test results indicate no significant differences between initial and revised texts, resulting in minimal variance between comparison pairs. Moreover, no significant differences were found between the pre-and post-writing assessment in all complexity measures. These findings suggest that providing feedback on students’ writing does not lead them to write less structurally complex texts. The syntactic complexity of their revised essays varied among high-, mid-, and low-achieving students. These variations could be attributed to proficiency levels, writing prompts, genre differences, and feedback sources. A discussion of pedagogical implications is provided.

Linguistic Features of Korean EFL Learners’ Writing: Based on Writing Quality and Genre

The present study examines the linguistic features of Korean college students’ English writings in terms of their writing quality and genre. Forty-eight Korean college students took part in the study, and their writing samples, comprised of narrative and exposition compositions, were collected to analyze on the basis of fluency and syntactic complexity. A total of 95 writings were entered into the computer program L2 syntactic complexity analyzer (L2SCA), and then statistical analyses such as ANOVA and t-test were performed to investigate how the linguistic features of the participants’ English writings are different depending on their writing quality and genre. The results showed that participants’ writing quality had a statistically significant impact on the text length of their writings, while it did not have a statistically significant effect on 13 measures out of 14 syntactic complexity measures. However, the results of genre differences indicated that the genre of writing had a substantial impact on 15 measures including fluency and syntactic complexity in the participants’ writing. Based on the results, some implications on how English writing instruction can better help Korean learners develop their English writing skills are discussed in the end.

Task complexity, task repetition, and L2 writing complexity: exploring interactions in the TBLT domain

Abstract Considering the increasing application of task-based frameworks to second language (L2) writing research, there has been a pressing need to examine TBLT views on the interactions between task conceptualization, task performance, and L2 writing outcomes. To address this need, the present study was designed to explore the synergistic effects of task complexity and task repetition on different facets of syntactic complexity as a key construct of proficiency and development in L2 writing. In doing so, 96 ESL learners performed written argumentative task versions with varying cognitive complexity in a counterbalanced fashion and then complete a task difficulty questionnaire. Afterward, they repeated the tasks in the opposite order at a one-week interval. The essays were analyzed using fine-grained syntactic complexity measures (reported by Lu’s L2 syntactic complexity analyzer, 2010). Linear mixed-effects models indicated significant main effects of task complexity and task repetition on different facets of syntactic complexity with robust effect sizes. However, no significant interaction effect between task complexity and task repetition was observed. These findings provide a reliable and accurate understanding of how syntactic complexity plays a role in the current accounts of connections between task features, implementation variables, and L2 writing task performance.

Mapping out the disciplinary variation of syntactic complexity in student academic writing

This study investigated disciplinary variation with respect to syntactic complexity in students' written academic texts from the British Academic Written English (BAWE) corpus. We measured syntactic complexity using the Tool for Automatic Analysis of Syntactic Sophistication and Complexity and then conducted quantitative and qualitative analyses to examine the disciplinary differences across four disciplinary groups and 31 disciplines. The analyses identified statistically significant variation in length, subordination, coordination, phrasal sophistication, and overall sentence complexity among the disciplinary groups as well as disciplines, which was discussed from a form-function mapping perspective. This study also revealed the systematic variation and form-function mappings of syntactic complexity in discipline-specific academic writing in both disciplinary groups and disciplines. Pedagogically, these findings can be incorporated into the curriculum design and class instruction to cultivate students’ discipline-specific academic literacy.

The Syntax of Climate Change: Syntactic Means in the Construction of Greta Thunberg’s Community Identity on Facebook

"The Syntax of Climate Change: Syntactic Means in the Construction of Greta Thunberg’s Community Identity on Facebook. It is argued that the identity of an online community (e.g., a Facebook community) is manifested by linguistic devices, such as syntactic means (Androutsopoulos 2015; Blumenfeld-Jones 2022; Kapranov 2019). This contention is explored in the study that is further presented and discussed in the article. The study seeks to identify syntactic means, in particular dependent clauses, which are involved in the construction of Greta Thunberg’s community identity on Facebook. Greta Thunberg, a famous climate change activist from Sweden, has a public account on Facebook that is followed by a substantial number of Facebook users, who, presumably, share her views on climate change, sustainability, and other environmental issues. It is assumed in the study that Greta Thunberg’s status updates on her public Facebook account could be characterised by syntactic means that facilitate the construction of the climate activists’ community identity. In order to verify the assumption, a corpus of Greta Thunberg’s status updates on Facebook was collected and analysed by the software program L2 Syntactic Complexity Analyzer (Lu 2010). The computer-assisted analysis was supplemented by a manual procedure of identifying the types of dependent clauses in the corpus. The results of the corpus analysis revealed that Greta Thunberg’s community construction on Facebook was facilitated by such syntactic means as dependent clauses, in particular non-finite, adverbial, and relative clauses. The findings were further discussed in the article through the lens of the construction of community identity. Keywords: climate change, dependent clauses, Facebook, Greta Thunberg, identity, online community, syntactic means "

TAASSC 프로그램을 활용하여 원어민과 한국인 대학생이 작성한 에세이에 나타난 명사구 복잡성의 특징 비교

This study investigates how syntactic features can be used to distinguish essays written by Korean college students from NS college students. Essays from the ICNALE(International Corpus Network of Asian Learners of English) corpus were analyzed using TAASSC(the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity) program. Two statistical analyses were performed. First, a multivariate analysis of variance(MANOVA) was employed to examine whether there are statistically significant differences in noun phrase complexity features between NS and Korean students. Second, a stepwise discriminant function analysis was performed to classify into two groups(i.e., NS and Korean students) in terms of noun phrase complexity features. Results showed that Korean and NS students significantly differed in terms of various noun phrase complexity indices. The best four predictors for distinguishing Korean students’ essays from NS students’ essays were dependents per object of the preposition, relative clause modifier per nominal, prepositions per object of the preposition, and dependents per nominal. It was shown that NS students produced more syntactically complex essays than Korean students by employing phrasal embedding. Implications of this study for English writing instruction are discussed.

The effects of genre on the syntactic complexity of argumentative and expository writing by Chinese EFL learners.

Genre researchers have found that writing in different genres involves different cognitive task loads and requires different linguistic demands. Generally speaking, narratives involve the description of events with a focus on people and their actions within a specific time frame, whereas non-narrative genres focus on making an argument or discussing ideas or beliefs in a logical fashion, thus resulting in distinct language features. However, the vast majority of genre-based studies have either focused on one single genre or made comparisons between narrative and non-narrative writing (mostly argumentative) in academic contexts without examining how EFL writers perform across non-narrative genres. Moreover, the measures used in quantifying the syntactic complexity of writing are varied, leading to inconsistent findings. This study investigated the effects of genre on the syntactic complexity of writing through comparing argumentative and expository compositions written by Chinese English-as-a-foreign-language (EFL) learners over one academic year. Fifty-two participants were asked to write eight compositions (with two genres alternated), four argumentative and four expository, which were parsed via the Syntactic Complexity Analyzer. The results with time as the within-subjects variable showed a significant development of syntactic complexity in both argumentative and expository compositions over one academic year. Meanwhile, the paired-sample t-test with genre as the within-subjects variable exhibited a higher syntactic complexity in argumentative compositions than in expository ones on most of the 14 measures examined at four time points over the year. Additionally, a two-way repeated measures analysis of variance with genre and time as independent variables ascertained an interactional effect of time and genre on some of the 14 measures. The present study tested and verified the impact genre exerts on the syntactic complexity of writing, providing implications for teachers to be more informed in teaching and assessing EFL writing and for students to be more conscious of genre difference in EFL writing.

A Corpus-Based Comparative Study on Syntactic Complexity in University Students’ EFL Writing in Southwestern China: A Case of Pu’er University

Syntactic complexity is the variety and sophistication degree of the syntactic structures conveyed in written production. The syntactic complexity of general Chinese university students’ EFL writing has been studied previously, but the performance of university students in educationally underdeveloped Southwestern China remains unclear. Taking Pu’er University as a case, this study collected 400 EFL compositions from 100 university students in Southwestern China and compared them with 200 writing samples from the Louvain Corpus of Native English Essays. Scores of 11 syntactic complexity indices were calculated using the L2 Syntactic Complexity Analyzer. The independent samples t-test was conducted to investigate whether and the extent to which the two groups differed on syntactic complexity indices. The results showed that university EFL students in Southwestern China produce a similar length of linguistic units when compared to native English writers. However, the amount of subordination in EFL writing is significantly less than that of native English writers. For the amount of coordination, the university EFL students produced a lower proportion of coordinate phrases than that of native writers, but the proportion of coordinate sentences is not significantly different between the two groups. Finally, for degree of phrasal sophistication, university EFL students in Southwestern China produce significantly fewer complex nominals than native writers do. The results imply that university students in Southwestern China should write more subordinated sentences and complex nominals, such as nominal clauses, infinitives, or gerunds, in their future EFL writing, instead of writing long sentences just heavily relying on simple coordination.

Dynamic development of syntactic complexity in second language writing: A longitudinal case study of a young Chinese EFL learner.

The present study analyzes the English diaries written by a young Chinese English as a foreign language (EFL) learner over a 1-year period in an attempt to determine the developmental process of Chinese EFL young learners’ written language in terms of syntactic complexity. This study aimed to use a wide range of metrics to explore densely collected data based on Dynamic Systems Theory. The longitudinal study data were analyzed through eight large-grained measures related to sentential, clausal, and phrasal features by using L2 Syntactic Complexity Analyzer, as well as fine-grained measures related to seven modifiers, an adjective placed before a noun, ordinal numerals are indicated (ADJA), cardinal numeral (CARD), predicative adjective, adverbial adjective (ADJP), adverbs (ADV), prepositional phrases (PREP), subordinate (SUB), and relative clause (REL), through manual annotations. The results show that, first, the developmental process was not linear but spiral in terms of large-grained measures. The sentential level varied, and the development process of the young learner is different from Chinese English learners studying in colleges. Second, the dynamic features of fine-grained measures are also prominent in the seven indicators. ADJA, PREP, and REL showed a steady increase, ADJP showed an obvious decline, while ADV and SUB first increased and then declined. Third, the correlation analysis revealed a competitive interaction within fine-grained measures and between large-grained and fine-grained measures.

Analysis of Syntactic Complexity and Semantic Coherence of Academic English Writing Based on Particle Swarm Optimization

Writing is an important part of testing language ability, and it is urgent to find some objective indicators to determine and evaluate the surface language structure, which will help language learners’ better master the target language. Complexity and semantic coherence are considered to be an important factor in the teaching of second language writing. In practice, due to the complexity of English writing syntax, such as a large number of high-dimensional nonlinear optimization problems, a new intelligent evaluation method is needed to solve them. At present, particle swarm optimization (PSO) has been widely used in function optimization, neural network training, combinatorial optimization, and other fields. This paper studies the syntactic complexity and semantic coherence of academic English writing based on PSO. The number of phrases is related to writing achievement. When the number of experiments reaches 25, the significant values of syntactic complexity and semantic coherence of data mining algorithm, artificial intelligence algorithm, decision tree algorithm, and PSO algorithm are 0.008, 0.003, 0.002, and 0.013, respectively, which shows that PSO algorithm is the best among them.