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Found 30 papers, 7 papers with code
HurtBERT: Incorporating Lexical Features with BERT for the Detection of Abusive Language
The detection of abusive or offensive remarks in social texts has received significant attention in research.
Counter-TWIT: An Italian Corpus for Online Counterspeech in Ecological Contexts
This work describes the process of creating a corpus of Twitter conversations annotated for the presence of counterspeech in response to toxic speech related to axes of discrimination linked to sexism, racism and homophobia.
Annotating Errors and Emotions in Human-Chatbot Interactions in Italian
This paper describes a novel annotation scheme specifically designed for a customer-service context where written interactions take place between a given user and the chatbot of an Italian telecommunication company.
Italian NLP for Everyone: Resources and Models from EVALITA to the European Language Grid
The European Language Grid enables researchers and practitioners to easily distribute and use NLP resources and models, such as corpora and classifiers.
The World Literature Knowledge Graph
In this paper we present The World Literature Knowledge Graph, a semantic resource containing 194, 346 writers and 965, 210 works, specifically designed for exploring facts about literary works and authors from different parts of the world.
Wikibio: a Semantic Resource for the Intersectional Analysis of Biographical Events
The corpus, which includes 20 Wikipedia biographies, was compared with five existing corpora to train a model for the biographical event detection task.
The URW-KG: a Resource for Tackling the Underrepresentation of non-Western Writers
Digital media have enabled the access to unprecedented literary knowledge.
APPReddit: a Corpus of Reddit Posts Annotated for Appraisal
Despite the large number of computational resources for emotion recognition, there is a lack of data sets relying on appraisal models.
Whose Opinions Matter? Perspective-aware Models to Identify Opinions of Hate Speech Victims in Abusive Language Detection
Therefore, we need novel approaches to model conflicting perspectives and opinions coming from people with different personal and demographic backgrounds.
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification
We present DEGARI (Dynamic Emotion Generator And ReclassIfier), an explainable system for emotion attribution and recommendation.
Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality
As a contribution to personality detection in languages other than English, we rely on distant supervision to create Personal-ITY, a novel corpus of YouTube comments in Italian, where authors are labelled with personality traits.
Personal-ITY: A Novel YouTube-based Corpus for Personality Prediction in Italian
We present a novel corpus for personality prediction in Italian, containing a larger number of authors and a different genre compared to previously available resources.
#Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection
Interest has grown around the classification of stance that users assume within online debates in recent years.
Do You Really Want to Hurt Me? Predicting Abusive Swearing in Social Media
In this study, we explore the phenomenon of swearing in Twitter conversations, taking the possibility of predicting the abusiveness of a swear word in a tweet context as the main investigation perspective.
FlorUniTo@TRAC-2: Retrofitting Word Embeddings on an Abusive Lexicon for Aggressive Language Detection
This paper describes our participation to the TRAC-2 Shared Tasks on Aggression Identification.
An Impossible Dialogue! Nominal Utterances and Populist Rhetoric in an Italian Twitter Corpus of Hate Speech against Immigrants
The paper proposes an investigation on the role of populist themes and rhetoric in an Italian Twitter corpus of hate speech against immigrants.
Cross-domain and Cross-lingual Abusive Language Detection: A Hybrid Approach with Deep Learning and a Multilingual Lexicon
This makes abusive language detection a domain-dependent task, and building a robust system to detect general abusive content a first challenge.
SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
The paper describes the organization of the SemEval 2019 Task 5 about the detection of hate speech against immigrants and women in Spanish and English messages extracted from Twitter.
Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation Structure
On this line, a new shared task has been proposed at SemEval-2017 (Task 8, SubTask A), which is focused on rumour stance classification in English tweets.
ValenTO at SemEval-2018 Task 3: Exploring the Role of Affective Content for Detecting Irony in English Tweets
In this paper we describe the system used by the ValenTO team in the shared task on Irony Detection in English Tweets at SemEval 2018.
SemEval 2018 Task 2: Multilingual Emoji Prediction
This paper describes the results of the first Shared Task on Multilingual Emoji Prediction, organized as part of SemEval 2018.
\#NonDicevoSulSerio at SemEval-2018 Task 3: Exploiting Emojis and Affective Content for Irony Detection in English Tweets
This paper describes the participation of the {\#}NonDicevoSulSerio team at SemEval2018-Task3, which focused on Irony Detection in English Tweets and was articulated in two tasks addressing the identification of irony at different levels of granularity.
Exploring the Impact of Pragmatic Phenomena on Irony Detection in Tweets: A Multilingual Corpus Study
This paper provides a linguistic and pragmatic analysis of the phenomenon of irony in order to represent how Twitter{'}s users exploit irony devices within their communication strategies for generating textual contents.
Friends and Enemies of Clinton and Trump: Using Context for Detecting Stance in Political Tweets
Stance detection, the task of identifying the speaker's opinion towards a particular target, has attracted the attention of researchers.
Annotating Sentiment and Irony in the Online Italian Political Debate on \#labuonascuola
In this paper we present the TWitterBuonaScuola corpus (TW-BS), a novel Italian linguistic resource for Sentiment Analysis, developed with the main aim of analyzing the online debate on the controversial Italian political reform {``}Buona Scuola{''} (Good school), aimed at reorganizing the national educational and training systems.
Tweeting and Being Ironic in the Debate about a Political Reform: the French Annotated Corpus TWitter-MariagePourTous
The annotation process is presented and the disagreement discussed, in particular, in the perspective of figurative language use and in that of the semantic oriented annotation, which are open challenges for NLP systems.
