As part of our ongoing endeavour to expand the possible mappings in Concepticon, I introduce an extended concept list of Vietnamese based on the Intercontinental Dictionary Series (IDS). The list includes elicitation glosses for 1,310 concepts that can be used as a reference to add more data or for comparative analyses. Here, I present the creation of the list and its content.
The ability to visualize data in an intelligible way is an important skill for scientists. In linguistics, especially in lexical semantics, data are often visualized using graphs, i.e., networks. For example, in the web app for the Database of Cross-Linguistic Colexifications (CLICS), we use networks to illustrate that a lexical form refers to two different concepts by connecting the concepts (i.e., nodes) with a line (i.e., edge). When identifying the colexifications between concepts across a large number of languages, the network grows and a tool to visualize multiple data points becomes necessary. Here, I present a tutorial for the first steps to visualize a colexification network with Cytoscape. The tutorial is intended for beginners who want to learn how the tool works and serves as a starting point for further skill development.
Reading, summarizing, and citing literature is an essential part of every student and researcher’s life. While there are many books and workshops on academic writing, there is less information on how to efficiently organize literature. For this reason, I offer an overview of how to organize literature and notes in Zotero. Specifically, I illustrate some of my own workflows for organizing the literature for my dissertation. I also discuss general features of Zotero. The interested reader who wants to learn more will benefit from the related links.
Colexification describes the relation between two meanings that are expressed with the same form in a given language. A colexification is established based on a linguistic analysis of word meanings in the same language. While the term is a cover term for different semantic relations (i.e., vagueness, polysemy, homophony), the discussion of particular types of colexifications often is connected to linguistic terminologies such as metaphor or metonymy. This is not only the case because there are prominent linguistic theories that argue for the pervasiveness of metaphor (and metonymy) in everyday life, but also because semantic relations are assumed to mirror conceptual relations. The linguistic analysis of metaphor and metonymy thus provides insights into the human mind. However, one needs to be careful to make claims about cognitive mechanisms solely based on linguistic evidence. Therefore, it is important to also consider frameworks from psychology such as analogical reasoning in order to explain the processes behind a linguistic phenomenon. In the following, I discuss ideas on metaphor and metonymy from linguistics that highlight the cognitive underpinnings of both notions, as well as a proposal for how analogical reasoning can explain their processing.
In recent years, studies exploring the phenomenon of colexification across languages have steadily increased in number. Colexification occurs if a word has multiple meanings, regardless of whether the meanings are related (dish ‘plate; meal’) or unrelated (bank ‘financial institution; part of a river’). The investigation of cross-linguistic colexifications yields many interesting findings that are important for different research fields. Psychologists and cognitive scientists are interested in the overarching principles that establish a connection between meanings and how speakers categorize the environment around them. Historical linguists are concerned with diachronic processes that lead to semantic shifts and what these can tell us about language evolution. Typologists engage in the study of language contact scenarios and how linguistic areas are formed. All these processes are entwined with one another and disentangling them is a challenge. This blog post is the first step into a deeper exploration of the origins of cross-linguistic colexifications and discusses the four processes underlying this phenomenon.
The Computer Language Comparison in Practice blog has grown steadily over the past few years. Each year we had a number of blog posts written by our colleagues on various topics. With the introduction of a PDF copy for every blog post and the publication of an annual volume, these blog posts can be treated like publications in a non-peer-reviewed journal. We hope that our blog will continue to be a valuable publication venue for our colleagues, not only those working in our research group and department, but also outside collaborators, and scholars who are generally interested in the topic and want to share their ideas. To maintain a coherent structure for all posts, this blog post provides a style guide for all future posts. Continue reading
Many words have multiple meanings, especially words for body parts. Some languages call the branch of a tree arm and others refer to the roof with the word head. These are instances of colexifications between body and object concepts and they occur across various languages. However, languages vary in terms of the frequency of body~object colexifications in their lexicon. It is, therefore, important to understand the different drivers that can lead to body~object colexifications. One possible factor to consider is the degree of how visually conspicuous a part of the body is. In an ongoing project, I investigate the role of visual salience as a driving force behind body~object colexifications. This blog post gives a brief overview and introduces the concept list that is the basis for my study.
In a recent blogpost (Tjuka 2021), I introduced a list of color, emotion, and human body part concepts. The list is the basis for a study on colexifications across three semantic domains. The first version of the list included 192 concepts. Of these concepts, 34 were from the emotion domain. We decided to add 28 additional emotion concepts to the list because this will allow us to further improve our analysis and compare our results with previous studies on emotion semantics. This blog post introduces the extended list.
In a recent blog post, I introduced the Database of Cross-Linguistic Norms, Ratings, and Relations for Words and Concepts (NoRaRe) and demonstrated how to add new data sets (Tjuka 2021). The database currently includes 65 unique word and concept properties based on 98 different data sets across 40 languages (NoRaRe v0.2, Tjuka et al. 2021a) and can easily be expanded further. But what can we do with the data? The article presenting the NoRaRe database already included three case studies that illustrate the application of the database (Tjuka et al. 2021b). This blog post, therefore, provides a tutorial on how to compare NoRaRe data sets in R by conducting a new case study that correlates ratings on arousal in English and Dutch.
Color, emotion, and human body parts are often considered universal semantic domains. However, cross-linguistic comparison of the connections within each of the domains reveals interesting differences across languages (e.g., Jackson et al. 2019). Researchers in lexical typology systematically collect the names for colors, emotions, and human body parts across various languages and analyze the principles of how naming patterns evolve. Using the same word for multiple concepts or colexification, for example, Vietnamese xanh denoting the colors green and blue, is often discussed in those studies. To study the colexifications across the three semantic domains color, emotion, and human body part, we need a set of comparable concepts. This blog post introduces a list of 192 concepts across all three domains based on the available concept sets in Concepticon (List et al. 2016, 2021).
There has been much discussion about the reproducibility of research and how it can be improved (Munafò et al. 2017). One antidote to the “reproducibility crisis” seems obvious: data sharing. However, one additional point that is not mentioned as often is the standardization of shared data to make them comparable. Especially for cross-linguistic studies, this is an important step that needs to take place so that we can conduct reproducible studies in different languages. The NoRaRe database (Tjuka et al. 2021a) is a resource that provides standardized cross-linguistic data on norms, ratings, and relations published in psychology and linguistics. In this blog post, I describe a beginner’s guide to adding data sets to NoRaRe.
In the summer of 2018, I set out to collect data for my master’s thesis (Tjuka 2019). The goal was to elicit body part terms that can also refer to object and landscape features. This was BC (before COVID-19), so I was able to meet with informants living in Berlin at the time and conduct my urban fieldwork study. The informants who participated in the study spoke one of 13 different languages (e.g., Wolof, Vietnamese, Czech). As a first task, I elicited 28 body part terms to get a sense of the naming patterns in each language. This blog post provides background information and introduces the resulting multilingual body part concept list.
In 2016, the Concepticon was introduced as a reference catalog for linguistic data of various kinds (List et al. 2016). The aim of the Concepticon project is to collect concept lists and link the glosses in the lists to unified concept sets (List et al. 2016; List et al. 2020). The project is a collaborative effort and the group of editors is constantly adding new data to the Concepticon (https://concepticon.clld.org/). In 2019, we implemented a review process that works similar to a submission process at an academic journal and is improving the quality of the resource in many ways. This blog post describes our effort to improve data validity by reviewing every single concept list that is added to the Concepticon. The database is curated openly on GitHub, so you can follow our review process by looking at several examples here: https://github.com/concepticon/concepticon-data
Over the past year, the doctoral students of our department have been organizing a weekly journal club. For me as a linguist, the discussions of various research articles opened up a whole new perspective on science in general and linguistics in particular. I learned about the interests and viewpoints of my fellow doctoral students and other researchers in our department working on historical linguistics, language documentation, and cultural evolution. In addition, organizing a journal club also helped me learn how to spark and lead a discussion. I hope the following personal insights offer some ideas and guidelines on how you can organize a journal club of your own.
I noticed that scientists deal with digital communication very differently: some avoid all sorts of platforms, others are much more present and involved in the discussions that are taking place in the online world. Digital communication as a linguist (or scientist in general) also includes sharing your research output. This does not have to be an article in a high-ranking journal. As a student, you can start by publishing your thesis, conference presentation slides, or a preprint. In this post, I’ll illustrate some of the possibilities that linguists and other researchers have to discuss and share their work.
