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Found 32 papers, 4 papers with code
Sifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety
Sifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety.
CyberAgressionAdo-v1: a Dataset of Annotated Online Aggressions in French Collected through a Role-playing Game
Over the past decades, the number of episodes of cyber aggression occurring online has grown substantially, especially among teens.
Extraction d’arguments basée sur les transformateurs pour des applications dans le domaine de la santé (Transformer-based Argument Mining for Healthcare Applications)
Nous présentons des résumés en français et en anglais de l’article (Mayer et al., 2020) présenté à la conférence 24th European Conference on Artificial Intelligence (ECAI-2020) en 2020.
“Don’t discuss”: Investigating Semantic and Argumentative Features for Supervised Propagandist Message Detection and Classification
One of the mechanisms through which disinformation is spreading online, in particular through social media, is by employing propaganda techniques.
Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain
While these LLMs display competitive performance on automated medical texts benchmarks, they have been pre-trained and evaluated with a focus on a single language (English mostly).
Argument Quality Assessment in the Age of Instruction-Following Large Language Models
The computational treatment of arguments on controversial issues has been subject to extensive NLP research, due to its envisioned impact on opinion formation, decision making, writing education, and the like.
Regrexit or not Regrexit: Aspect-based Sentiment Analysis in Polarized Contexts
As a step in the aforementioned direction, we present a methodology to extend the task of Aspect-based Sentiment Analysis (ABSA) toward the affect and emotion representation in polarized settings.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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Hybrid Emoji-Based Masked Language Models for Zero-Shot Abusive Language Detection
Recent studies have demonstrated the effectiveness of cross-lingual language model pre-training on different NLP tasks, such as natural language inference and machine translation.
A Dataset Independent Set of Baselines for Relation Prediction in Argument Mining
Argument Mining is the research area which aims at extracting argument components and predicting argumentative relations (i. e., support and attack) from text.
Love Me, Love Me, Say (and Write!) that You Love Me: Enriching the WASABI Song Corpus with Lyrics Annotations
We present the WASABI Song Corpus, a large corpus of songs enriched with metadata extracted from music databases on the Web, and resulting from the processing of song lyrics and from audio analysis.
Comparing Automated Methods to Detect Explicit Content in Song Lyrics
The Parental Advisory Label (PAL) is a warning label that is placed on audio recordings in recognition of profanity or inappropriate references, with the intention of alerting parents of material potentially unsuitable for children.
Song Lyrics Summarization Inspired by Audio Thumbnailing
Given the peculiar structure of songs, applying generic text summarization methods to lyrics can lead to the generation of highly redundant and incoherent text.
A System to Monitor Cyberbullying based on Message Classification and Social Network Analysis
Social media platforms like Twitter and Instagram face a surge in cyberbullying phenomena against young users and need to develop scalable computational methods to limit the negative consequences of this kind of abuse.
Yes, we can! Mining Arguments in 50 Years of US Presidential Campaign Debates
We address this task in an empirical manner by annotating 39 political debates from the last 50 years of US presidential campaigns, creating a new corpus of 29k argument components, labeled as premises and claims.
Graph Data on the Web: extend the pivot, don't reinvent the wheel
Wimmics stands for Web-Instrumented Man-Machine Interactions, Communities, and Semantics.
SMILK, linking natural language and data from the web
As part of the SMILK Joint Lab, we studied the use of Natural Language Processing to: (1) enrich knowledge bases and link data on the web, and conversely (2) use this linked data to contribute to the improvement of text analysis and the annotation of textual content, and to support knowledge extraction.
Evidence Type Classification in Randomized Controlled Trials
Randomized Controlled Trials (RCT) are a common type of experimental studies in the medical domain for evidence-based decision making.
Lyrics Segmentation: Textual Macrostructure Detection using Convolutions
Lyrics contain repeated patterns that are correlated with the repetitions found in the music they accompany.
Measuring Frame Instance Relatedness
Frame semantics is a well-established framework to represent the meaning of natural language in computational terms.
You'll Never Tweet Alone: Building Sports Match Timelines from Microblog Posts
In this paper, we propose an approach to build a timeline with actions in a sports game based on tweets.
Building timelines of soccer matches from Twitter
This demo paper presents a system that builds a timeline with salient actions of a soccer game, based on the tweets posted by users.
Graph-based Event Extraction from Twitter
Detecting which tweets describe a specific event and clustering them is one of the main challenging tasks related to Social Media currently addressed in the NLP community.
Argument Mining on Twitter: Arguments, Facts and Sources
Social media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in.
DART: a Dataset of Arguments and their Relations on Twitter
The problem of understanding the stream of messages exchanged on social media such as Facebook and Twitter is becoming a major challenge for automated systems.
Challenges in Bridging Social Semantics and Formal Semantics on the Web
This paper describes several results of Wimmics, a research lab which names stands for: web-instrumented man-machine interactions, communities, and semantics.
Towards a Benchmark of Natural Language Arguments
The connections among natural language processing and argumentation theory are becoming stronger in the latest years, with a growing amount of works going in this direction, in different scenarios and applying heterogeneous techniques.
Classifying Inconsistencies in DBpedia Language Specific Chapters
We define the LingRel ontology to represent how the extracted information from different chapters is related to each other, and we map the properties of the LingRel ontology to the properties of the SIOC-Argumentation ontology to built argumentation graphs.
