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Found 18 papers, 10 papers with code
Embedding Structured Dictionary Entries
Previous work has shown how to effectively use external resources such as dictionaries to improve English-language word embeddings, either by manipulating the training process or by applying post-hoc adjustments to the embedding space.
Computational valency lexica and Homeric formularity
But can we use distributional semantics to study a language with such a limited corpus as ancient Greek?
DUKweb: Diachronic word representations from the UK Web Archive corpus
Lexical semantic change (detecting shifts in the meaning and usage of words) is an important task for social and cultural studies as well as for Natural Language Processing applications.
Semantic Journeys: Quantifying Change in Emoji Meaning from 2012-2018
The semantics of emoji has, to date, been considered from a static perspective.
DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages
Word meaning is notoriously difficult to capture, both synchronically and diachronically.
Lexical semantic change for Ancient Greek and Latin
In this chapter we build on GASC, a recent computational approach to semantic change based on a dynamic Bayesian mixture model.
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
Lexical Semantic Change detection, i. e., the task of identifying words that change meaning over time, is a very active research area, with applications in NLP, lexicography, and linguistics.
Living Machines: A study of atypical animacy
This paper proposes a new approach to animacy detection, the task of determining whether an entity is represented as animate in a text.
Analyzing Temporal Relationships between Trending Terms on Twitter and Urban Dictionary Activity
However, it is unclear exactly how activity on this platform relates to larger conversations happening elsewhere on the web, such as discussions on larger, more popular social media platforms.
Urban Dictionary Embeddings for Slang NLP Applications
The choice of the corpus on which word embeddings are trained can have a sizable effect on the learned representations, the types of analyses that can be performed with them, and their utility as features for machine learning models.
Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings
Word embeddings are increasingly used for the automatic detection of semantic change; yet, a robust evaluation and systematic comparison of the choices involved has been lacking.
Mining the UK Web Archive for Semantic Change Detection
Semantic change detection (i. e., identifying words whose meaning has changed over time) started emerging as a growing area of research over the past decade, with important downstream applications in natural language processing, historical linguistics and computational social science.
The citation advantage of linking publications to research data
Efforts to make research results open and reproducible are increasingly reflected by journal policies encouraging or mandating authors to provide data availability statements.
Digital Libraries
GASC: Genre-Aware Semantic Change for Ancient Greek
Word meaning changes over time, depending on linguistic and extra-linguistic factors.
Extracting Keywords from Open-Ended Business Survey Questions
Open-ended survey data constitute an important basis in research as well as for making business decisions.
Pilot study for the COST Action "Reassembling the Republic of Letters": language-driven network analysis of letters from the Hartlib's Papers
The present report summarizes an exploratory study which we carried out in the context of the COST Action IS1310 "Reassembling the Republic of Letters, 1500-1800", and which is relevant to the activities of Working Group 3 "Texts and Topics" and Working Group 2 "People and Networks".
Emo, Love, and God: Making Sense of Urban Dictionary, a Crowd-Sourced Online Dictionary
On the one hand, the promise of the "wisdom of the crowd" has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based information in many languages.
