Quantifying Systemic Coupling and Syndrome Using Multivariate Statistical Methods: An SFL Corpus Example

2021 ◽  
Author(s):  
Bandar Alhumaidi A. Almutairi
Keyword(s):  
Statistical Methods ◽  
Correspondence Analysis ◽  
Systemic Functional Linguistics ◽  
Multiple Correspondence Analysis ◽  
Linear Analysis ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Log Linear ◽  
Online Debate ◽  
The Relationship

One of the fundamental underpinnings of systemic functional linguistics (SFL) is that the relationship between language-as-system and language-as-text is modelled probabilistically in relation to the cline of instantiation. This offers a spectrum of new ways to approach several SFL concepts quantitatively. This paper falls within that spectrum as it proposes that the relatively recent concepts of coupling and syndrome can be redefined quantitatively in relation to instantiation through two statistical methods – namely log-linear analysis and multiple correspondence analysis (MCA) The application of these two methods is illustrated through an analysis of a corpus of twelve online voting-based online debate texts (ODTs) The results and discussion sections of this paper show that the methods can identify and quantify significant couplings and syndromes from both probabilistic and statistical perspectives. Both methods illustratively highlight eleven couplings and four syndromes associated with the more persuasive and less persuasive ODTs writers.

Application of the multiple correspondence analysis for the evaluation of rain event characteristics influence on rainfall interception

2020 ◽  
Author(s):  
Katarina Zabret ◽  
Mojca Šraj
Keyword(s):  
Wind Speed ◽  
Correspondence Analysis ◽  
Multiple Correspondence Analysis ◽  
Pinus Nigra ◽  
Rainfall Amount ◽  
Rain Event ◽  
Rainfall Interception ◽  
Multivariate Statistical ◽  
Pine Trees ◽  
The Relationship

<p>Rainfall interception by birch (<em>Betula pendula</em> Roth.) and pine (<em>Pinus nigra</em> Arnold) trees was measured in small urban park in the city of Ljubljana, Slovenia from beginning of the year 2014. Three and a half years of measurements of throughfall, stemflow and rainfall in the open were analyzed to estimate the influence of rain event characteristics on rainfall interception. A new approach using multiple correspondence analysis (MCA) was implemented. MCA is a multivariate statistical method for descriptive rather than quantitative variables, and can be used to estimate the relationship between the variables. The results are presented using diagrams, in which the proximity of the variables corresponds to their interdependence and the location of the variables (positive or negative domain) corresponds to their positive or negative correlation. The analysis included information from 176 events, showing the relationship between rainfall interception of birch and pine trees and rainfall amount, duration and intensity, wind speed and direction, drop number and median volume diameter (MVD), expressing raindrop size. The numerical values of the variables were transformed to the descriptive ones using classes regarding the threshold values of the variables (more or less than threshold), which was determined through sensitivity analysis. The thresholds were 6 mm for rainfall amount, 4 h for duration and 1.8 mm/h for intensity, 1.3 m/s for wind speed, 8 cardinal directions for wind direction, 1.5 mm for MVD and 10,000, 50,000 and 100,000 raindrops for their number. The MCA again showed the dominant influence of the rainfall amount, as the ratio of rainfall interception to rainfall amount decreases with increasing rainfall amounts. MCA including the wind characteristics gave a new insight into its influence on rainfall interception. The results expressed two new directions of occasional wind corridor according to the nearby buildings which were not visible using other methods of data analyses. The presented analysis, using MCA, confirmed results of previous analyses using other methods and offered a new insights into the process.</p>

scholarly journals Using Multiple Correspondence Analysis to Evaluate Selected Aspects of Behaviour of Consumers Purchasing Local Food Products

2017 ◽  
Vol 65 (6) ◽  
pp. 2083-2093
Author(s):  
Petra Šánová ◽  
Jitka Svobodová ◽  
Adriana Laputková
Keyword(s):  
Correspondence Analysis ◽  
Local Food ◽  
Consumer Preferences ◽  
Multiple Correspondence Analysis ◽  
Food Products ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
The Czech Republic ◽  
Nutritional Values ◽  
Marketing Activities

The paper compares selected aspects of behaviour of consumers when purchasing local food products in the Czech Republic or food products labelled as local or regional using correspondence analysis vis‑ŕ‑vis customer gender. Its purpose is to identify aspects which each group of the consumers (that is men vs. women) consider important when purchasing local food products. Information about the preferences of customers purchasing local food is important for marketing activities of retailers and producers. Data from 269 respondents have been processed in total according to gender and purchasing frequency. Correspondence analysis was used in order to evaluate consumer preferences and to identify their behaviour. MCA is an exploratory multivariate statistical analysis that allows investigation of several qualitative parameters. Appearance and information on the packaging, qualitative parameters (visually declared), anticipated health benefits and declared nutritional values were the focus of the research. This paper is significant in terms of using sign schemes, correlation and correspondence analysis, therefore the analysis demonstrates differences in these aspects between men’s and women’s behaviour when purchasing local food products inter alia, according to their purchasing frequency, which previous papers have not considered while using multivariate statistical methods.

Null se constructions in Brazilian and European Portuguese: morphosyntactic deletion or emergence of new constructions?

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Augusto Soares da Silva ◽  
Susana Afonso ◽  
Dafne Palú ◽  
Karlien Franco
Keyword(s):  
Statistical Methods ◽  
External Factors ◽  
Important Predictor ◽  
Cognitive Grammar ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Passive Construction ◽  
European Portuguese ◽  
Change Of State ◽  
The Moment

Abstract Se constructions designate a set of polysemous constructions along a transitivity continuum marked by the clitic se that perform various functions: reflexive/reciprocal, middle, anticausative, passive, and impersonal. A counterpart of these constructions without the clitic – the null se construction – is also attested. Based on an extensive usage-feature and profile-based analysis, and using multivariate statistical methods, we analyze, considering Cognitive Grammar, the conceptual, structural, and lectal factors that determine the choice between overt and null se constructions. The results of the study show that the null constructions are far more frequent in Brazilian (BP) than in European Portuguese (EP). In BP, the focus on the moment of change is a crucial factor for the overt/null variation in reflexive/reciprocal, middle, anticausative, and impersonal constructions. If the moment of the change of state is profiled, the overt se construction is usually produced. If the moment of change is not profiled, the null se construction is preferred. External factors also play a role in the variation. Register is an important predictor for the observed variation of the anticausative construction, and the only predictor for the overt/null variation in the case of the passive construction. In EP, the null se variant is mainly limited to anticausative constructions. In all cases of null constructions, there is a shift to an absolute construal, which has an impact on the way that the transitivity continuum is conceptualized.

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