Search Results for author:
Found 43 papers, 3 papers with code
Combining Language Models and Linguistic Information to Label Entities in Memes
This paper describes the system we developed for the shared task ‘Hero, Villain and Victim: Dissecting harmful memes for Semantic role labelling of entities’ organised in the framework of the Second Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situation (Constraint 2022).
When the Student Becomes the Master: Learning Better and Smaller Monolingual Models from mBERT
In this research, we present pilot experiments to distil monolingual models from a jointly trained model for 102 languages (mBERT).
D-Terminer: Online Demo for Monolingual and Bilingual Automatic Term Extraction
This contribution presents D-Terminer: an open access, online demo for monolingual and multilingual automatic term extraction from parallel corpora.
Annotating Topics, Stance, Argumentativeness and Claims in Dutch Social Media Comments: A Pilot Study
This pilot study reports on the annotation of a corpus of 100 Dutch user comments made in response to politically-themed news articles on Facebook.
Investigating the Quality of Static Anchor Embeddings from Transformers for Under-Resourced Languages
This paper reports on experiments for cross-lingual transfer using the anchor-based approach of Schuster et al. (2019) for English and a low-resourced language, namely Hindi.
Irony Detection for Dutch: a Venture into the Implicit
This paper presents the results of a replication experiment for automatic irony detection in Dutch social media text, investigating both a feature-based SVM classifier, as was done by Van Hee et al. (2017) and and a transformer-based approach.
SentEMO: A Multilingual Adaptive Platform for Aspect-based Sentiment and Emotion Analysis
In this paper, we present the SentEMO platform, a tool that provides aspect-based sentiment analysis and emotion detection of unstructured text data such as reviews, emails and customer care conversations.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
A Pilot Study for BERT Language Modelling and Morphological Analysis for Ancient and Medieval Greek
This paper presents a pilot study to automatic linguistic preprocessing of Ancient and Byzantine Greek, and morphological analysis more specifically.
LT3 at SemEval-2021 Task 6: Using Multi-Modal Compact Bilinear Pooling to Combine Visual and Textual Understanding in Memes
Internet memes have become ubiquitous in social media networks today.
LT3 at SemEval-2020 Task 8: Multi-Modal Multi-Task Learning for Memotion Analysis
Internet memes have become a very popular mode of expression on social media networks today.
LT3 at SemEval-2020 Task 7: Comparing Feature-Based and Transformer-Based Approaches to Detect Funny Headlines
This paper presents two different systems for the SemEval shared task 7 on Assessing Humor in Edited News Headlines, sub-task 1, where the aim was to estimate the intensity of humor generated in edited headlines.
LT3 at SemEval-2020 Task 9: Cross-lingual Embeddings for Sentiment Analysis of Hinglish Social Media Text
The second approach incorporates pre-trained English embeddings that are incrementally retrained with a set of Hinglish tweets.
Identifying Cognates in English-Dutch and French-Dutch by means of Orthographic Information and Cross-lingual Word Embeddings
This paper investigates the validity of combining more traditional orthographic information with cross-lingual word embeddings to identify cognate pairs in English-Dutch and French-Dutch.
Sentiment Analysis for Hinglish Code-mixed Tweets by means of Cross-lingual Word Embeddings
We specifically investigate the use of these embeddings for a sentiment analysis task for Hinglish Tweets, viz.
TermEval 2020: Shared Task on Automatic Term Extraction Using the Annotated Corpora for Term Extraction Research (ACTER) Dataset
The TermEval 2020 shared task provided a platform for researchers to work on automatic term extraction (ATE) with the same dataset: the Annotated Corpora for Term Extraction Research (ACTER).
Current Limitations in Cyberbullying Detection: on Evaluation Criteria, Reproducibility, and Data Scarcity
The detection of online cyberbullying has seen an increase in societal importance, popularity in research, and available open data.
Analysing the Impact of Supervised Machine Learning on Automatic Term Extraction: HAMLET vs TermoStat
Traditional approaches to automatic term extraction do not rely on machine learning (ML) and select the top n ranked candidate terms or candidate terms above a certain predefined cut-off point, based on a limited number of linguistic and statistical clues.
A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information
This paper presents proof-of-concept experiments for combining orthographic and semantic information to distinguish cognates from non-cognates.
LT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval)
This paper describes our contribution to the SemEval-2019 Task 5 on the detection of hate speech against immigrants and women in Twitter (hatEval).
We Usually Don't Like Going to the Dentist: Using Common Sense to Detect Irony on Twitter
Although common sense and connotative knowledge come naturally to most people, computers still struggle to perform well on tasks for which such extratextual information is required.
Economic Event Detection in Company-Specific News Text
This paper presents a dataset and supervised classification approach for economic event detection in English news articles.
SemEval-2018 Task 3: Irony Detection in English Tweets
Our shared tasks received submissions from 43 teams for the binary classification Task A and from 31 teams for the multiclass Task B.
Automatic Detection of Cyberbullying in Social Media Text
While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online.
Towards an integrated pipeline for aspect-based sentiment analysis in various domains
This paper presents an integrated ABSA pipeline for Dutch that has been developed and tested on qualitative user feedback coming from three domains: retail, banking and human resources.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
Monday mornings are my fave :) \#not Exploring the Automatic Recognition of Irony in English tweets
Recognising and understanding irony is crucial for the improvement natural language processing tasks including sentiment analysis.
A Classification-based Approach to Economic Event Detection in Dutch News Text
Breaking news on economic events such as stock splits or mergers and acquisitions has been shown to have a substantial impact on the financial markets.
Exploring the Realization of Irony in Twitter Data
Handling figurative language like irony is currently a challenging task in natural language processing.
Evaluation of Automatic Hypernym Extraction from Technical Corpora in English and Dutch
In this research, we evaluate different approaches for the automatic extraction of hypernym relations from English and Dutch technical text.
Discovering Missing Wikipedia Inter-language Links by means of Cross-lingual Word Sense Disambiguation
The input for the inter-language link detection system is a set of Dutch pages for a given ambiguous noun and the output of the system is a set of links to the corresponding pages in three target languages (viz.
