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Found 36 papers, 13 papers with code
Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators’ Disagreement
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media.
Weigh Your Own Words: Improving Hate Speech Counter Narrative Generation via Attention Regularization
Regularized models produce better counter narratives than state-of-the-art approaches in most cases, both in terms of automatic metrics and human evaluation, especially when hateful targets are not present in the training data.
Benchmarking the Generation of Fact Checking Explanations
Results show that in justification production summarization benefits from the claim information, and, in particular, that a claim-driven extractive step improves abstractive summarization performances.
Human-Machine Collaboration Approaches to Build a Dialogue Dataset for Hate Speech Countering
Fighting online hate speech is a challenge that is usually addressed using Natural Language Processing via automatic detection and removal of hate content.
Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study
In this work, we present an extensive study on the use of pre-trained language models for the task of automatic Counter Narrative (CN) generation to fight online hate speech in English.
Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media.
Multilingual Counter Narrative Type Classification
The growing interest in employing counter narratives for hatred intervention brings with it a focus on dataset creation and automation strategies.
Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech
Undermining the impact of hateful content with informed and non-aggressive responses, called counter narratives, has emerged as a possible solution for having healthier online communities.
Empowering NGOs in Countering Online Hate Messages
In this paper, we introduce a novel ICT platform that NGO operators can use to monitor and analyze social media data, along with a counter-narrative suggestion tool.
Towards Knowledge-Grounded Counter Narrative Generation for Hate Speech
Tackling online hatred using informed textual responses - called counter narratives - has been brought under the spotlight recently.
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.
Toward Stance-based Personas for Opinionated Dialogues
In the context of chit-chat dialogues it has been shown that endowing systems with a persona profile is important to produce more coherent and meaningful conversations.
GePpeTto Carves Italian into a Language Model
We provide a thorough analysis of GePpeTto's quality by means of both an automatic and a human-based evaluation.
Generating Counter Narratives against Online Hate Speech: Data and Strategies
Recently research has started focusing on avoiding undesired effects that come with content moderation, such as censorship and overblocking, when dealing with hatred online.
Generating Challenge Datasets for Task-Oriented Conversational Agents through Self-Play
End-to-end neural approaches are becoming increasingly common in conversational scenarios due to their promising performances when provided with sufficient amount of data.
CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech
Although there is an unprecedented effort to provide adequate responses in terms of laws and policies to hate content on social media platforms, dealing with hatred online is still a tough problem.
FASTDial: Abstracting Dialogue Policies for Fast Development of Task Oriented Agents
We present a novel abstraction framework called FASTDial for designing task oriented dialogue agents, built on top of the OpenDial toolkit.
Generating E-Commerce Product Titles and Predicting their Quality
The setting requires the generation process to be fast and the generated title to be both human-readable and concise.
DepecheMood++: a Bilingual Emotion Lexicon Built Through Simple Yet Powerful Techniques
Several lexica for sentiment analysis have been developed and made available in the NLP community.
A Methodology for Evaluating Interaction Strategies of Task-Oriented Conversational Agents
In task-oriented conversational agents, more attention has been usually devoted to assessing task effectiveness, rather than to \textit{how} the task is achieved.
Toward zero-shot Entity Recognition in Task-oriented Conversational Agents
We present a domain portable zero-shot learning approach for entity recognition in task-oriented conversational agents, which does not assume any annotated sentences at training time.
Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines
In this paper, we describe a methodology to infer Bullish or Bearish sentiment towards companies/brands.
Why Do Urban Legends Go Viral?
In particular we will focus on the idea that urban legends should mimic the details of news (who, where, when) to be credible, while they should be emotional and readable like a fairy tale to be catchy and memorable.
SentiWords: Deriving a High Precision and High Coverage Lexicon for Sentiment Analysis
Using this technique we have built SentiWords, a prior polarity lexicon of approximately 155, 000 words, that has both a high precision and a high coverage.
Echoes of Persuasion: The Effect of Euphony in Persuasive Communication
While the effect of various lexical, syntactic, semantic and stylistic features have been addressed in persuasive language from a computational point of view, the persuasive effect of phonetics has received little attention.
Deep Feelings: A Massive Cross-Lingual Study on the Relation between Emotions and Virality
This article provides a comprehensive investigation on the relations between virality of news articles and the emotions they are found to evoke.
DepecheMood: a Lexicon for Emotion Analysis from Crowd-Annotated News
While many lexica annotated with words polarity are available for sentiment analysis, very few tackle the harder task of emotion analysis and are usually quite limited in coverage.
Creative language explorations through a high-expressivity N-grams query language
In computation linguistics a combination of syntagmatic and paradigmatic features is often exploited.
Is it morally acceptable for a system to lie to persuade me?
Given the fast rise of increasingly autonomous artificial agents and robots, a key acceptability criterion will be the possible moral implications of their actions.
Sentiment Analysis: How to Derive Prior Polarities from SentiWordNet
Assigning a positive or negative score to a word out of context (i. e. a word's prior polarity) is a challenging task for sentiment analysis.
Brand Pitt: A Corpus to Explore the Art of Naming
The name of a company or a brand is the key element to a successful business.
