scholarly journals That’s Cool. Computational Sociolinguistic Methods for Investigating Individual Lexico-grammatical Variation

2021 ◽  
Vol 3 ◽  
Author(s):  
Hans-Jörg Schmid ◽  
Quirin Würschinger ◽  
Sebastian Fischer ◽  
Helmut Küchenhoff
Keyword(s):  
Individual Variation ◽  
Regression Models ◽  
Semantic Information ◽  
Language Change ◽  
Data Driven ◽  
Social Variables ◽  
Ideal Position ◽  
Social Variation ◽  
Grammatical Variation

The present study deals with variation in the use of lexico-grammatical patterns and emphasizes the need to embrace individual variation. Targeting the pattern that’s adj (as in that’s right, that’s nice or that’s okay) as a case study, we use a tailor-made Python script to systematically retrieve grammatical and semantic information about all instances of this construction in BNC2014 as well as sociolinguistic information enabling us to study social and individual lexico-grammatical variation among speakers who have used this pattern. The dataset amounts to 4,394 tokens produced by 445 speakers using 159 adjective types in 931 conversations. Using detailed descriptive statistics and mixed-effects regression models, we show that while the choice of some adjectives is partly determined by social variables, situational and especially individual variation is rampant overall. Adopting a cognitive-linguistic perspective and relying on the notion of entrenchment, we interpret these findings as reflecting individual speakers' routines. We argue that computational sociolinguistics is in an ideal position to contribute to the data-driven investigation of individual lexico-grammatical variation and encourage computational sociolinguists to grab this opportunity. For the routines of individual speakers ultimately both underlie and compromise systematic social variation and trigger and steer well-known types of language change including grammaticalization, pragmaticalization and change by invited inference.

Usualization

2020 ◽  
pp. 124-177
Author(s):  
Hans-Jörg Schmid
Keyword(s):  
Individual Variation ◽  
Language Change ◽  
Sociology Of Knowledge ◽  
Linguistic Variation ◽  
Unified Approach ◽  
Constructivist Model

The chapter discusses the nature of the process of usualization and explains its contribution to the conventionalization of innovations, to linguistic variation, change, and persistence. The process is explained with reference to Berger and Luckmann’s (1966) constructivist model of the sociology of knowledge. Usualization is responsible for the conventionalization of innovative form-meaning pairings as well as innovative forms and meanings. It is argued that linguistic variation on all dimensions, from form, structure, and meaning to situational, social, and individual variation can be handled by the unified approach suggested by the EC-Model. Usualization is a major factor in types of language change labelled by such terms as grammaticalization, lexicalization, pragmaticalization, idiomatization, and context-induced change. A case study of the development of the going-to future illustrates this potential. Not only variation and change, but also the persistence of structure are dynamic in the sense that it must be refreshed by continual usualization.

Scales and Units

2018 ◽  
Author(s):  
Kathryn M. de Luna
Keyword(s):  
Language Change ◽  
Historical Linguistics ◽  
Bantu Languages ◽  
The North ◽  
First Case ◽  
Linguistic Evidence ◽  
River Region ◽  
History Of ◽  
Alternative Approaches

This chapter uses two case studies to explore how historians study language movement and change through comparative historical linguistics. The first case study stands as a short chapter in the larger history of the expansion of Bantu languages across eastern, central, and southern Africa. It focuses on the expansion of proto-Kafue, ca. 950–1250, from a linguistic homeland in the middle Kafue River region to lands beyond the Lukanga swamps to the north and the Zambezi River to the south. This expansion was made possible by a dramatic reconfiguration of ties of kinship. The second case study explores linguistic evidence for ridicule along the Lozi-Botatwe frontier in the mid- to late 19th century. Significantly, the units and scales of language movement and change in precolonial periods rendered visible through comparative historical linguistics bring to our attention alternative approaches to language change and movement in contemporary Africa.

scholarly journals Digital Storytelling in Cultural Heritage: Audience Engagement in the Interactive Documentary New Life

2021 ◽  
Vol 13 (3) ◽  
pp. 1193
Author(s):  
Anna Podara ◽  
Dimitrios Giomelakis ◽  
Constantinos Nicolaou ◽  
Maria Matsiola ◽  
Rigas Kotsakis
Keyword(s):  
Cultural Heritage ◽  
Full Range ◽  
Social Dimension ◽  
Data Driven ◽  
Specific Interest ◽  
Key Factors ◽  
Audience Engagement ◽  
Main Research ◽  
The Social

This paper casts light on cultural heritage storytelling in the context of interactive documentary, a hybrid media genre that employs a full range of multimedia tools to document reality, provide sustainability of the production and successful engagement of the audience. The main research hypotheses are enclosed in the statements: (a) the interactive documentary is considered a valuable tool for the sustainability of cultural heritage and (b) digital approaches to documentary storytelling can provide a sustainable form of viewing during the years. Using the Greek interactive documentary (i-doc) NEW LIFE (2013) as a case study, the users’ engagement is evaluated by analyzing items from a seven-year database of web metrics. Specifically, we explore the adopted ways of the interactive documentary users to engage with the storytelling, the depth to which they were involved along with the most popular sections/traffic sources and finally, the differences between the first launch period and latest years were investigated. We concluded that interactivity affordances of this genre enhance the social dimension of cultural, while the key factors for sustainability are mainly (a) constant promotion with transmedia approach; (b) data-driven evaluation and reform; and (c) a good story that gathers relevant niches, with specific interest to the story.

scholarly journals Multiple target data-driven models to enable sustainable process manufacturing: An industrial bioprocess case study

2021 ◽  
Vol 296 ◽  
pp. 126242
Author(s):  
Oliver J. Fisher ◽  
Nicholas J. Watson ◽  
Laura Porcu ◽  
Darren Bacon ◽  
Martin Rigley ◽  
...  
Keyword(s):  
Data Driven ◽  
Multiple Target ◽  
Process Manufacturing ◽  
Target Data

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

scholarly journals Research on a novel data-driven aging estimation method for battery systems in real-world electric vehicles

2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110277
Author(s):  
Yankai Hou ◽  
Zhaosheng Zhang ◽  
Peng Liu ◽  
Chunbao Song ◽  
Zhenpo Wang
Keyword(s):  
Electric Vehicles ◽  
Real World ◽  
Regression Models ◽  
Estimation Method ◽  
Recursive Least Squares ◽  
Data Driven ◽  
Accurate Estimation ◽  
Support Vector ◽  
Battery Degradation ◽  
Operational Data

Accurate estimation of the degree of battery aging is essential to ensure safe operation of electric vehicles. In this paper, using real-world vehicles and their operational data, a battery aging estimation method is proposed based on a dual-polarization equivalent circuit (DPEC) model and multiple data-driven models. The DPEC model and the forgetting factor recursive least-squares method are used to determine the battery system’s ohmic internal resistance, with outliers being filtered using boxplots. Furthermore, eight common data-driven models are used to describe the relationship between battery degradation and the factors influencing this degradation, and these models are analyzed and compared in terms of both estimation accuracy and computational requirements. The results show that the gradient descent tree regression, XGBoost regression, and light GBM regression models are more accurate than the other methods, with root mean square errors of less than 6.9 mΩ. The AdaBoost and random forest regression models are regarded as alternative groups because of their relative instability. The linear regression, support vector machine regression, and k-nearest neighbor regression models are not recommended because of poor accuracy or excessively high computational requirements. This work can serve as a reference for subsequent battery degradation studies based on real-time operational data.

scholarly journals Organisational Constraints in Data-driven Maintenance: a case study in the automotive industry

2020 ◽  
Vol 53 (3) ◽  
pp. 95-100
Author(s):  
P Savolainen ◽  
J Magnusson ◽  
M. Gopalakrishnan ◽  
E. Turanoglu Bekar ◽  
A. Skoogh
Keyword(s):  
Automotive Industry ◽  
Data Driven

scholarly journals A Method for Assessing Threats to the Economic Security of a Region: A Case Study of Public Procurement in Russia

Risks ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 10
Author(s):  
Valentina Kravchenko ◽  
Tatiana Kudryavtseva ◽  
Yuriy Kuporov
Keyword(s):  
Regression Models ◽  
Public Procurement ◽  
Ordinary Least Squares ◽  
Economic Security ◽  
Government Procurement ◽  
Security Monitoring ◽  
Significant Relationships ◽  
Monitoring Tools ◽  
Russian Region

The issue of economic security is becoming an increasingly urgent one. The purpose of this article is to develop a method for assessing threats to the economic security of the Russian region. This method is based on step-by-step actions: first of all, choosing an element of the region’s economic security system and collecting its descriptive indicators; then grouping indicators by admittance-process-result categories and building hypotheses about their influence; testing hypotheses using a statistical package and choosing the most significant connections, which can pose a threat to the economic security of the region; thereafter ranking regions by the level of threats and developing further recommendations. The importance of this method is that with the help of grouping regions (territory of a country) based on proposed method, it is possible to develop individual economic security monitoring tools. As a result, the efficiency of that country’s region can be higher. In this work, the proposed method was tested in the framework of public procurement in Russia. A total of 14 indicators of procurement activity were collected for each region of the Russian Federation for the period from 2014 to 2018. Regression models were built on the basis of the grouped indicators. Ordinary Least Squares (OLS) Estimation was used. As a result of pairwise regression models analysis, we have defined four significant relationships between public procurement indicators. There are positive connections between contracts that require collateral and the percentage of tolerances, between the number of bidders and the number of regular suppliers, between the number of bidders and the average price drop, and between the number of purchases made from a single supplier and the number of contracts concluded without reduction. It was determined that the greatest risks for the system were associated with the connection between competition and budget savings. It was proposed to rank analyzed regions into four groups: ineffective government procurement, effective government procurement, and government procurement that threatens the system of economic security of the region, that is, high competition with low savings and low competition with high savings. Based on these groups, individual economic security monitoring tools can be developed for each region.

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