Avoiding Information Overload — Ways of Exemplifying in Bilingual e-Dictionaries Depending on the Systematicity of the Linguistic Data

Although monolingual dictionaries have received more academic attention, bilingual dictionaries are essential for learners at all levels. Today's electronic dictionaries for language learning have no space limitations, so the information they offer can be exhaustive. This brings with it the risk of information overload — users may feel overwhelmed and find it difficult to find the information they are looking for. E-dictionary editors must therefore balance comprehensiveness with usability and decide which linguistic data to present. Since examples are the entry component that takes up the most space, several types of examples are considered, and the systematicity of the information to be presented is the criterion for adopting specific lexicographic solutions. Research shows that shorter examples, such as infinitive phrases, support generalisable patterns, while full sentences and supplementary examples highlight more complex, unpredictable uses. This article proposes an innovative type of example, the translated cotext item, to help users infer usage rules. Ultimately, the study emphasises that dictionaries should help learners to intuitively distinguish predictable structures from language-specific expressions, thereby enhancing their ability to use the target language idiomatically. Keywords: information overload, usability, electronic bilingual lexicography, entry components, dictionary example, language systematicity

Authors

Institutions

Publication Details

Journal
Lexikos
Published
2025-01-01
DOI
https://doi.org/10.5788/35-1-2028
Primary Topic
Lexicography and Language Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Avoiding Information Overload — Ways of Exemplifying in Bilingual e-Dictionaries Depending on the Systematicity of the Linguistic Data

Alfonso Rascón Caballero
Lexikos
Lexicography and Language Studies
article

Avoiding Information Overload — Ways of Exemplifying in Bilingual e-Dictionaries Depending on the Systematicity of the Linguistic Data

Alfonso Rascón Caballero
article en

Abstract

Although monolingual dictionaries have received more academic attention, bilingual dictionaries are essential for learners at all levels. Today's electronic dictionaries for language learning have no space limitations, so the information they offer can be exhaustive. This brings with it the risk of information overload — users may feel overwhelmed and find it difficult to find the information they are looking for. E-dictionary editors must therefore balance comprehensiveness with usability and decide which linguistic data to present. Since examples are the entry component that takes up the most space, several types of examples are considered, and the systematicity of the information to be presented is the criterion for adopting specific lexicographic solutions. Research shows that shorter examples, such as infinitive phrases, support generalisable patterns, while full sentences and supplementary examples highlight more complex, unpredictable uses. This article proposes an innovative type of example, the translated cotext item, to help users infer usage rules. Ultimately, the study emphasises that dictionaries should help learners to intuitively distinguish predictable structures from language-specific expressions, thereby enhancing their ability to use the target language idiomatically. Keywords: information overload, usability, electronic bilingual lexicography, entry components, dictionary example, language systematicity

LexikosVol. 35
Vilnius University (LT), Vilnius University of Applied Sciences (LT)
Openalex Percentile: Top 87%
Lexicography and Language Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.