Linguistic Distance Measures Research Articles

The economics of L2 English. Evidence from 2.0 mln subjects suggests an economics of language framework to account for country differences in L2 English proficiency

ABSTRACT We analysed Education First’s Standard English Test scores coming from 2 mln learners of English in 109 countries world-wide. Proficiency in English as a global lingual franca is an important skill in various areas of international communication. A larger linguistic distance between English as a second language and a learner’s first language has been put forward as increasing the efforts or costs of learning English. Instead of the subjective measures used in the past, we constructed a quantitative linguistic distance measure based on comparing words (lexicon), constructions (morpho-syntax), and sounds (phonology) between English and 59 mother tongues. Mixed regression analyses were carried out on the countries’ proficiency scores with a country’s human capital index, the official status of English in a country, and linguistic distance as predictors. All three predictors turn out to be robust proficiency determinants. Language skills constitute an essential component of human resources in today’s emerging and growing knowledge economy. These skills cannot be taken for granted and additional language training is required when linguistic distances are large.

Associations of students’ linguistic distance to the language of instruction and classroom composition with English reading and listening skills

AbstractGlobally classrooms are increasingly linguistically diverse. Research often oversimplifies lived linguistic heterogeneity as binary variables: native versus non-native. Linguistic distance (LD) measures allow a fine-grained operationalization of linguistic diversity in foreign language education. This study investigated associations of cognate LDs of students’ home languages and classroom heterogeneity with English as a Foreign Language skills. Data were collected from a diverse sample of 5,130 Year 5 students in Germany. Mixed-effects linear models confirmed our hypotheses that higher individual LDs and a higher proportion of multilingual learners per classroom were both independently associated with lower English proficiency. Multilingual learners with higher cognate LDs to English and students in more linguistically heterogeneous classrooms had lower English proficiency. The results emphasize the need to assess LD in research to better differentiate between students. Foreign language classrooms seem not to address linguistic diversity adequately and need to readjust their focus to better meet multilingual learners’ needs.

Generalized q-rung picture linguistic aggregation operators and their application in decision making

The q-rung picture linguistic set (q-RPLS) is an effective tool for managing complex and unpredictable information by changing the parameter ‘q’ regarding hesitancy degree. In this article, we devise some generalized operational laws of q-RPLS in terms of the Archimedean t-norm and t-conorm. Based on the proposed generalized operations, we define two types of generalized aggregation operators, namely the q-rung picture linguistic averaging operator and the q-rung picture linguistic geometric operator, and study their relevant characteristics in-depth. With a view toward applications, we discuss certain specific cases of the proposed generalized aggregation operators with a range of parameter values. Furthermore, we explore q-rung picture linguistic distance measure and its required axioms. Then we put forward a technique for q-RPLSs based on the proposed aggregation operators and distance measure to solve multi-attribute decision-making (MADM) challenges with unknown weight information. At last, a practical example is presented to demonstrate the suggested approaches’ viability and to perform the sensitivity and comparison analysis.

Robot Selection Using An Integrated MAGDM Model Based on ELECTRE Method and Linguistic q-Rung Orthopair Fuzzy Information

With the development of engineering sciences, many companies are using robots in different industries to improve the efficiency and accuracy of their work. However, the need for robots under different requirements is different, which makes the selection of robots complex. In this paper, a linguistic q-rung orthogonal fuzzy multiple attribute group decision-making (MAGDM) method based on ELECTRE is proposed for robot selection. First, the basic Hausdorff distance is extended to the linguistic q-rung orthopair fuzzy environment to measure the deviation between two linguistic q-rung orthopair fuzzy numbers and two linguistic q-rung orthopair fuzzy sets. Then, the properties of the linguistic q-rung orthopair fuzzy distance measure based on Hausdorff distance are investigated. In addition, two maximum deviation models for deriving the weights of decision-makers and attributes are proposed. Moreover, a new MAGDM method is proposed by extending the ELECTRE method to the linguistic q-rung orthopair fuzzy environment. Finally, the practicality as well as the effectiveness of the method is demonstrated through a case study of the robot selection problem. The linguistic q-rung distance measure is used to construct two maximum deviation models to objectively derive the weights of attributes and decision-makers, and the linguistic q-rung orthopair fuzzy ELECTRE method is used to complete the selection of robots for a clean energy company. Furthermore, the sensitivity analysis of the parameter in the proposed method is provided, and the superiority of the new method is illustrated by the comparison with existing MAGDM methods.

An integrated hesitant fuzzy linguistic model for multiple attribute group decision-making for health management center selection

Eliciting information in multiple attribute group decision-making (MAGDM) is a key for obtaining more reliable results in decisions defined under uncertain domains. In this case, the use of a hesitant fuzzy linguistic term set (HFLTS) as a flexible model to express decision-makers’ (DMs’) qualitative and hesitant decision-making information has been successfully applied to multiple decision situations. However, in many decision situations, DMs’ and attributes’ weights are still subjectively provided. These actions may cause randomness of decision results. Therefore, to solve the two issues, this paper aims to develop a group consensus optimization model and DEA (data envelopment analysis) model to derive DMs’ weights and attributes’ weights, respectively, based on HFLTS. Hence, a new hesitant fuzzy linguistic distance measure is introduced first, and some properties are discussed. The individual consensus measure and the group consensus measure are then defined based on this hesitant fuzzy linguistic distance measure. Subsequently, a new group consensus optimization model is introduced and included in the DEA-based TODIM method for MAGDM with HFLTSs. This integrated approach is applied in health management center site selection. Finally, a sensitivity and a comparative analysis with other methods such as hesitant fuzzy linguistic VIKOR and hesitant fuzzy linguistic TOPSIS are performed to show the validity of our proposed approach.

Linguistic Distance, Languages of Work and Wages of Immigrants in Montreal

We use the Levenshtein linguistic distance measure to explore the question of whether the distance between an immigrant’s mother tongue and a Canadian official language (English or French) has an impact on his/her economic integration into the labor market. Using microdata from the master files of the 2001 and 2006 Canadian censuses and from the 2011 National Household Survey, we investigate the relationship between linguistic distance and the intensity of use of English and French at work in the Montreal metropolitan area. That region is characterized by the presence of sizeable French- and English-speaking communities, as well as by a large number of immigrants from a wide variety of linguistic backgrounds. Those elements of linguistic diversity interact in the environment of English being the lingua franca. We find that linguistic distances between immigrants’ mother tongues and English and French have an important impact on the relative intensities of use of the two Canadian official languages at work. We further investigate the role of the languages used at work on the earnings of immigrants by estimating earnings functions. We find that the use of both French and English is remunerated positively in the labor market, but that using English at work has a larger impact on earnings.

Network consensus analysis of probabilistic linguistic preference relations for group decision making and its application in urban household waste classification

The selection of the urban household waste classification rules is important to both city sustainability and clean production of enterprises using the renewable urban household waste, but few studies focused on it. Probabilistic linguistic preference relations have been proposed to express both quantitative and qualitative preference information, which attracted many researchers’ attention. For the consensus studies of probabilistic linguistic preference relations, current methods have two challenges regarding the information change in normalization and the information loss in integration. To overcome these challenges, from the perspective of experts’ networks under criteria, this study aims to propose a network consensus analysis of probabilistic linguistic preference relations based on a novel probabilistic linguistic Kolmogorov-Smirnov distance measure. To achieve this goal, the cumulative probability distributions of probabilistic linguistic term sets are introduced to define the probabilistic linguistic Kolmogorov-Smirnov distance measure. Based on this novel distance measure, an argument measurement and a programming with analytic solutions are proposed to group experts’ networks into three categories: the harmonious network, adjustable divergent network, and non-adjustable divergent network. The consensus degrees of these three kinds of networks are also given to get the consensus degrees of criteria. A fuzzy Cronbach’s alpha is presented to calculate the weights of criteria and the final consensus degree of a group. Given that the urban household waste classification rule selection is actually an multi-criteria group decision making problem, we then provide an illustration of selecting a suitable urban household waste classification rules to validate the applicability of the proposed method. Comparative analyses are provided to demonstrate the advantages and reliability of the network consensus analysis in selecting urban household waste classification rules.

A probabilistic linguistic-based deviation method for multi-expert qualitative decision making with aspirations

Probabilistic linguistic term set (PLTS) is a popular tool for modeling complex linguistic perceptions of decision-makers (DMs) and has gained successful applications in the field of multi-expert multi-criteria decision making (MEMCDM). In many probabilistic linguistic decision-making situations DMs are usually aspiration oriented in which the utilities of DMs do not depend on the absolute level of criteria values, but on the degree to which the criteria values match their aspirations levels. However, the aspirations of DMs are not considered in existing probabilistic linguistic decision making methods. One contribution of this paper is to introduce five probabilistic linguistic-based aspiration utility functions to take DMs’ aspirations into account. These functions can well describe the utility variation of DMs under different preference structures with the aspiration levels. Afterwards, the probabilistic linguistic-based indicator is defined to take into account the criteria weights represented by PLTSs, which greatly facilitates DMs to provide the weights of criteria, comparing with the use of crisp numbers. As the second contribution, we build a probabilistic linguistic-based deviation model to identify the decision results in MEMCDM. This model can achieve the goal that the decision results for group opinions are consistent with that for the individual DM’s opinions to the greatest extent. On the other hand, we also show with some counterexamples that the existing probabilistic linguistic distance measures are unreasonable. We present an improving distance measure for PLTSs and show its desirable properties. The biggest advantage of the developed distance measure is that it not only considers the deviation between the proportion information of linguistic terms but also takes into account linguistic terms themselves in PLTS.

Ancient Origins of the Global Variation in Economic Preferences

This paper shows that contemporary population-level heterogeneity in risk aversion, time preference, altruism, positive reciprocity, negative reciprocity, and trust partly traces back to the structure of the migration patterns of our very early ancestors. To document this pattern, we link differences in preferences between populations to the length of time elapsed since the ancestors of the respective groups broke apart from each other, as proxied by genetic and linguistic distance measures. Preference differences are significantly increasing in ancestral distance in both cross-country regressions and within-country analyses across groups of migrants.

Single-Valued Neutrosophic Linguistic-Induced Aggregation Distance Measures and Their Application in Investment Multiple Attribute Group Decision Making

This paper studied the single-valued neutrosophic linguistic distance measures based on the induced aggregation method. Firstly, we proposed a single-valued neutrosophic linguistic-induced ordered weighted averaging distance (SVNLIOWAD) measure, which is a new extension of the existing distance measures based on the induced aggregation view. Then, based on the proposed SVNLIOWAD, a novel induced distance for single-valued neutrosophic linguistic sets, namely the single-valued neutrosophic linguistic weighted induced ordered weighted averaging distance (SVNLWIOWAD), was developed to eliminate the defects of the existing methods. The relationship between the two proposed distance measures was also explored. A multiple attribute group decision making (MAGDM) model was further presented based on the proposed SVNLWIOWAD measure. Finally, a numerical example concerning an investment selection problem was provided to demonstrate the usefulness of the proposed method under a single-valued neutrosophic linguistic environment and, then, a comparison analysis was carried out to verify the flexibility and effectiveness of the proposed work.

Novel distance and similarity measures on hesitant fuzzy linguistic term sets with application to pattern recognition

As two important features of hesitant fuzzy linguistic term sets (HFLTSs), distance and similarity measures have been applied widely in many fields such as pattern recognition, decision making and prediction. Through analyzing the existing distance a

A Single-Valued Neutrosophic Linguistic Combined Weighted Distance Measure and Its Application in Multiple-Attribute Group Decision-Making

The aim of this paper is to present a multiple-attribute group decision-making (MAGDM) framework based on a new single-valued neutrosophic linguistic (SVNL) distance measure. By unifying the idea of the weighted average and ordered weighted averaging into a single-valued neutrosophic linguistic distance, we first developed a new SVNL weighted distance measure, namely a SVNL combined and weighted distance (SVNLCWD) measure. The focal characteristics of the devised SVNLCWD are its ability to combine both the decision-makers’ attitudes toward the importance, as well as the weights, of the arguments. Various desirable properties and families of the developed SVNLCWD were contemplated. Moreover, a MAGDM approach based on the SVNLCWD was formulated. Lastly, a real numerical example concerning a low-carbon supplier selection problem was used to describe the superiority and feasibility of the developed approach.

Probabilistic Linguistic MULTIMOORA: A Multicriteria Decision Making Method Based on the Probabilistic Linguistic Expectation Function and the Improved Borda Rule

The probabilistic linguistic term set (PLTS) is a powerful technique in representing linguistic evaluations of individuals or groups in the process of decision making. The aim of this paper is to propose a strongly robust method to solve multiexperts multicriteria decision making problems with linguistic evaluations. To enrich the computation and to improve the measures of PLTS, we first define an expectation function of it. In addition, we advance three kinds of probabilistic linguistic distance measures reflecting on the difference of linguistic terms and probabilities at the same time to make up for the defects of the existing distance measures, and then propose the similarity and correlation measures. Integrating the subjective opinions with the correlation coefficients between criteria, we put forward a combined weight determining method. The robustness of the ranking method, MULTIMOORA, is enhanced by the improved Borda rule. Based on these research findings, a probabilistic linguistic MULTIMOORA method is proposed. Finally, the developed method is applied to an empirical example concerning the selection of shared karaoke television brands. The effectiveness of the proposed method is verified by some comparative analyses.

Fermatean fuzzy linguistic set and its application in multicriteria decision making

In this paper, we propose the concept of Fermatean fuzzy linguistic term sets based on linguistic term sets and Fermatean fuzzy sets. The basic operational laws, the score function, and the accuracy function of Fermatean fuzzy linguistic numbers are provided. Then we propose the Fermatean fuzzy linguistic weighted aggregation operator, the Fermatean fuzzy linguistic weighted geometric operator, and the Fermatean fuzzy linguistic distance measures. Furthermore, we extend the TOPSIS method to the proposed distance measures, and the ranking of alternatives is obtained under a Fermatean fuzzy linguistic environment. An example is provided to illustrate the feasibility and effectiveness of the proposed method, and a comparison with the existing method is also analyzed. Finally, the sensitivity analysis of the parameter in the proposed distance measure is also discussed.

Cosine Distance Measure between Neutrosophic Hesitant Fuzzy Linguistic Sets and Its Application in Multiple Criteria Decision Making

This paper proposes a neutrosophic hesitant fuzzy linguistic term set (NHFLTS) based on hesitant fuzzy linguistic term set (HFLTS) and neutrosophic set (NS), which can express the inconsistent and uncertainty information flexibly in multiple criteria decision making problems. The basic operational laws of NHFLTS based on linguistic scale function are also discussed. Then we propose the generalized neutrosophic hesitant fuzzy linguistic distance measure and discuss its properties. Furthermore, a new similarity measure of NHFLTS combines the generalized neutrosophic hesitant fuzzy linguistic distance measure and the cosine function is given. A corresponding cosine distance measure between NHFLTSs is proposed according to the relationship between the similarity measure and the distance measure, and we develop the technique for order preference by similarity to an ideal solution (TOPSIS) method to the obtained cosine distance measure. The main advantages of the proposed NHFLTS is defined on linguistic scale function, the decision makers can flexibly convert the linguistic information to semantic values, and the proposed cosine distance measure between NHFLTSs with TOPSIS method can deal with the related decision information not only from the point of view of algebra, but also from the point of view of geometry. Finally, the reasonableness and effectiveness of the proposed method is demonstrated by the illustrative example, which is also compared to the other existing methods.

A Novel Comparative Linguistic Distance Measure Based on Hesitant Fuzzy Linguistic Term Sets and Its Application in Group Decision-Making

The linguistic approaches are required in order to assess qualitative aspects of many real problems. In most of these problems, decision makers only adopt single and very simple terms which would not reflect exactly what the experts mean for many intricate applications. Frequently, the assessments of decision making problems involve comparative linguistic expressions. Accordingly, we propose a novel distance measure between hesitant fuzzy linguistic term sets (HFLTSs) to solve fuzzy group decision making (FGDM) problems. Firstly we define the characteristic functions to describe the HFLTSs transformed from comparative linguistic expressions. Then we construct a weighted HFLTSs graph containing all notes in the HFLTSs. Distances in the graph of individual assessments are defined by measures considering diversity and specificity of HFLTS’s granularity. We put forward a new approach to achieve aggregation results for group decision making to realize the minimal distances with individual assessments. Finally, numerical examples are illustrated.

Several Generalized Interval-Valued 2-Tuple Linguistic Interval Distance Measures and Their Application

Interval-valued linguistic variables are efficient tools to express the decision makers’ uncertain qualitative judgments. Considering the application of interval-valued linguistic variables, this paper proposes an interval distance measure, which is then used to define interval-valued linguistic interval distance measures by combining the 2-tuple linguistic representation model. To reflect the interactions between elements in a set, three correlative interval distance measures on intervalvalued linguistic variables are proposed. Meanwhile, several models designed to obtain the optimal weighting vector are constructed. After that, an approach to pattern recognition and to multi-attribute decision making with interval-valued linguistic information is developed. Meanwhile, associated examples are offered to demonstrate the concrete application of the proposed procedure.

A Novel Probabilistic Linguistic Approach for Large-Scale Group Decision Making with Incomplete Weight Information

The large-scale group decision-making (GDM) problems with linguistic information have received more and more attentions; however, how to effectively manage the linguistic assessments provided by the large number of experts is still a challenge. In this paper, we employ the probabilistic linguistic term sets (PLTSs), which are the extension form of hesitant fuzzy linguistic term sets, to manage the large number of linguistic assessments. We also present a probabilistic linguistic distance measure for PLTSs. To address the large-scale probabilistic linguistic GDM problems in which the weights of groups are completely unknown or partially known in advance, we develop a probabilistic linguistic GDM method. First, we propose a consistency- and consensus-based model to objectively determine the weights of the groups. Then, to aggregate the opinions of all the groups, we propose a new probabilistic linguistic weighted arithmetic averaging operator and by using it the collective assessment of each alternative is obtained. Finally, the ranking of all alternatives is obtained on the basis of the dominance degrees and the optimal alternative is selected.

An improved MULTIMOORA approach for multi-criteria decision-making based on interdependent inputs of simplified neutrosophic linguistic information

Multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) is a useful method to apply in multi-criteria decision-making due to the flexibility and robustness it introduces into the decision process. This paper defines several simplified neutrosophic linguistic distance measures and employs a distance-based method to determine criterion weights. Then, an improved MULTIMOORA approach is presented by integrating the simplified neutrosophic linguistic normalized weighted Bonferroni mean and simplified neutrosophic linguistic normalized geometric weighted Bonferroni mean operators as well as a simplified neutrosophic linguistic distance measure. This approach ranks alternatives according to three ordering methods, and then, uses dominance theory to combine the three rankings into a single ranking. Finally, this paper presents a practical case example and conducts a comparative analysis between the proposed approach and existing methods in order to verify the feasibility and effectiveness of the developed methodology.

Commentary: Large-scale psychological differences within China explained by rice vs. wheat agriculture.

Commentary: Large-scale psychological differences within China explained by rice vs. wheat agriculture.