Simona Frenda | Università degli Studi di Torino (original) (raw)

Papers by Simona Frenda

Research paper thumbnail of A Multilingual Dataset of Racial Stereotypes in Social Media Conversational Threads

Findings of the Association for Computational Linguistics: EACL 2023

Research paper thumbnail of Detecting racial stereotypes: An Italian social media corpus where psychology meets NLP

Information Processing & Management

Research paper thumbnail of APPReddit: a Corpus of Reddit Posts Annotated for Appraisal

Research paper thumbnail of O-Dang! The Ontology of Dangerous Speech Messages

Research paper thumbnail of Killing me softly: Creative and cognitive aspects of implicitness in abusive language online

Natural Language Engineering

Abusive language is becoming a problematic issue for our society. The spread of messages that rei... more Abusive language is becoming a problematic issue for our society. The spread of messages that reinforce social and cultural intolerance could have dangerous effects in victims’ life. State-of-the-art technologies are often effective on detecting explicit forms of abuse, leaving unidentified the utterances with very weak offensive language but a strong hurtful effect. Scholars have advanced theoretical and qualitative observations on specific indirect forms of abusive language that make it hard to be recognized automatically. In this work, we propose a battery of statistical and computational analyses able to support these considerations, with a focus on creative and cognitive aspects of the implicitness, in texts coming from different sources such as social media and news. We experiment with transformers, multi-task learning technique, and a set of linguistic features to reveal the elements involved in the implicit and explicit manifestations of abuses, providing a solid basis for c...

Research paper thumbnail of Sarcasm and Implicitness in Abusive Language Detection: A Multilingual Perspective

Research paper thumbnail of Stance or insults?

Research paper thumbnail of Recognizing Hate with NLP: The Teaching Experience of the #DeactivHate Lab in Italian High Schools

The possibility of raising awareness about misbehaviour online, such as hate speech, especially i... more The possibility of raising awareness about misbehaviour online, such as hate speech, especially in young generations could help society to reduce their impact, and thus, their consequences. The Computer Science Department of the University of Turin has designed various technologies that support educational projects and activities in this perspective. We implemented an annotation platform for Italian tweets employed in a laboratory called #DEACTIVHATE, specifically designed for secondary school students. The laboratory aims at countering hateful phenomena online and making students aware of technologies that they use on a daily basis. We describe our teaching experience in high schools and the usefulness of the technologies and activities tested.

Research paper thumbnail of Overview of the EVALITA 2018 Task on Irony Detection in Italian Tweets (IronITA)

EVALITA Evaluation of NLP and Speech Tools for Italian, 2018

Research paper thumbnail of Ironic Gestures and Tones in Twitter

Proceedings of the Fourth Italian Conference on Computational Linguistics CLiC-it 2017, 2017

Research paper thumbnail of Automatic Expansion of Lexicons for Multilingual Misogyny Detection

EVALITA Evaluation of NLP and Speech Tools for Italian, 2018

Research paper thumbnail of Do Linguistic Features Help Deep Learning? The Case of Aggressiveness in Mexican Tweets

Computación y Sistemas, 2020

Research paper thumbnail of HaSpeeDe 2 @ EVALITA2020: Overview of the EVALITA 2020 Hate Speech Detection Task

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020, 2020

Research paper thumbnail of Computational rule-based model for Irony Detection in Italian Tweets

English. In the domain of Natural Language Processing (NLP), the interest in figurative language ... more English. In the domain of Natural Language Processing (NLP), the interest in figurative language is enhanced, especially in the last few years, thanks to the amount of linguistic data provided by web and social networks. Figurative language provides a non-literary sense to the words, thus the utterances require several interpretations disclosing the play of signification. In order to individuate different meaning levels in case of ironic texts detection, it is necessary a computational model appropriated to the complexity of rhetorical artifice. In this paper we describe our rulebased system of irony detection as it has been presented to the SENTIPOLC task of EVALITA 2016, where we ranked third on twelve participants. Italiano. Nell’ambito del Natural Language Processing (NLP) l’interesse per il linguaggio figurativo è particolarmente aumentato negli ultimi anni, grazie alla quantità d’informazione linguistica messa a disposizione dal web e dai social network. Il linguaggio figurati...

Research paper thumbnail of Exploration of Misogyny in Spanish and English Tweets

Nowadays, misogynistic abuse online has become a serious issue due, especially, to anonymity and ... more Nowadays, misogynistic abuse online has become a serious issue due, especially, to anonymity and interactivity of the web that facilitate the increase and the permanence of the offensive comments on the web. In this paper, we present an approach based on stylistic and specific topic information for the detection of misogyny, exploring the several aspects of misogynistic Spanish and English user generated texts on Twitter. Our method has been evaluated in the framework of our participation in the AMI shared task at IberEval 2018 obtaining promising results.

Research paper thumbnail of The role of sarcasm in hate speech.A multilingual perspective

The importance of the detection of aggressiveness in social media is due to real effects of viole... more The importance of the detection of aggressiveness in social media is due to real effects of violence provoked by negative behavior online. For this reason, hate speech online is a real problem in modern society and the necessity of control of usergenerated contents has become one of the priorities for governments, social media platforms and Internet companies. Current methodologies are far from solving this problem. Indeed, several aggressive comments are also disguised as sarcastic. In this perspective, this research proposal wants to investigate the role played by creative linguistic devices, especially sarcasm, in hate speech in multilingual context.

Research paper thumbnail of Deep Analysis in Aggressive Mexican Tweets

The importance of the detection of aggressiveness in social media is due to real effects of viole... more The importance of the detection of aggressiveness in social media is due to real effects of violence provoked by negative behavior online. Indeed, this kind of legal cases are increasing in the last years. For this reason, the necessity of controlling user-generated contents has become one of the priorities for many Internet companies, although current methodologies are far from solving this problem. Therefore, in this work we propose an innovative approach that combines deep learning framework with linguistic features specific for this issue. This approach has been evaluated and compared with other ones in the framework of the MEX-A3T shared task at IberEval on aggressiveness analysis in Spanish Mexican tweets. In spite of our novel approach, we obtained low results.

Research paper thumbnail of Computational Models for Irony Detection in Three Spanish Variants

The lack of understanding of figurative language online, such as ironic messages, is a common cau... more The lack of understanding of figurative language online, such as ironic messages, is a common cause of error for systems that analyze automatically the users’ opinions online detecting sentiment, emotions or stance. In order to deal with this problem of automatic processing of natural language, IroSvA shared task at IberLef 2019 asks participants to detect, for the first time, irony in short texts written in Spanish language, considering the three linguistic variants from Spain, Mexico and Cuba. Another novelty of this task is the presence of labels specifying the context of the utterance, such as current political or social issues discussed online. In the context of this shared task, we approached irony detection in Spanish short texts trying to exploit the provided topic information. In addition, we investigated the usefulness of stylistic, lexical and affective features during the development of the irony detection models for the three Spanish variants. Experimental results and f...

Research paper thumbnail of The unbearable hurtfulness of sarcasm

Expert Systems with Applications

Research paper thumbnail of Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter

Journal of Intelligent & Fuzzy Systems

Research paper thumbnail of A Multilingual Dataset of Racial Stereotypes in Social Media Conversational Threads

Findings of the Association for Computational Linguistics: EACL 2023

Research paper thumbnail of Detecting racial stereotypes: An Italian social media corpus where psychology meets NLP

Information Processing & Management

Research paper thumbnail of APPReddit: a Corpus of Reddit Posts Annotated for Appraisal

Research paper thumbnail of O-Dang! The Ontology of Dangerous Speech Messages

Research paper thumbnail of Killing me softly: Creative and cognitive aspects of implicitness in abusive language online

Natural Language Engineering

Abusive language is becoming a problematic issue for our society. The spread of messages that rei... more Abusive language is becoming a problematic issue for our society. The spread of messages that reinforce social and cultural intolerance could have dangerous effects in victims’ life. State-of-the-art technologies are often effective on detecting explicit forms of abuse, leaving unidentified the utterances with very weak offensive language but a strong hurtful effect. Scholars have advanced theoretical and qualitative observations on specific indirect forms of abusive language that make it hard to be recognized automatically. In this work, we propose a battery of statistical and computational analyses able to support these considerations, with a focus on creative and cognitive aspects of the implicitness, in texts coming from different sources such as social media and news. We experiment with transformers, multi-task learning technique, and a set of linguistic features to reveal the elements involved in the implicit and explicit manifestations of abuses, providing a solid basis for c...

Research paper thumbnail of Sarcasm and Implicitness in Abusive Language Detection: A Multilingual Perspective

Research paper thumbnail of Stance or insults?

Research paper thumbnail of Recognizing Hate with NLP: The Teaching Experience of the #DeactivHate Lab in Italian High Schools

The possibility of raising awareness about misbehaviour online, such as hate speech, especially i... more The possibility of raising awareness about misbehaviour online, such as hate speech, especially in young generations could help society to reduce their impact, and thus, their consequences. The Computer Science Department of the University of Turin has designed various technologies that support educational projects and activities in this perspective. We implemented an annotation platform for Italian tweets employed in a laboratory called #DEACTIVHATE, specifically designed for secondary school students. The laboratory aims at countering hateful phenomena online and making students aware of technologies that they use on a daily basis. We describe our teaching experience in high schools and the usefulness of the technologies and activities tested.

Research paper thumbnail of Overview of the EVALITA 2018 Task on Irony Detection in Italian Tweets (IronITA)

EVALITA Evaluation of NLP and Speech Tools for Italian, 2018

Research paper thumbnail of Ironic Gestures and Tones in Twitter

Proceedings of the Fourth Italian Conference on Computational Linguistics CLiC-it 2017, 2017

Research paper thumbnail of Automatic Expansion of Lexicons for Multilingual Misogyny Detection

EVALITA Evaluation of NLP and Speech Tools for Italian, 2018

Research paper thumbnail of Do Linguistic Features Help Deep Learning? The Case of Aggressiveness in Mexican Tweets

Computación y Sistemas, 2020

Research paper thumbnail of HaSpeeDe 2 @ EVALITA2020: Overview of the EVALITA 2020 Hate Speech Detection Task

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020, 2020

Research paper thumbnail of Computational rule-based model for Irony Detection in Italian Tweets

English. In the domain of Natural Language Processing (NLP), the interest in figurative language ... more English. In the domain of Natural Language Processing (NLP), the interest in figurative language is enhanced, especially in the last few years, thanks to the amount of linguistic data provided by web and social networks. Figurative language provides a non-literary sense to the words, thus the utterances require several interpretations disclosing the play of signification. In order to individuate different meaning levels in case of ironic texts detection, it is necessary a computational model appropriated to the complexity of rhetorical artifice. In this paper we describe our rulebased system of irony detection as it has been presented to the SENTIPOLC task of EVALITA 2016, where we ranked third on twelve participants. Italiano. Nell’ambito del Natural Language Processing (NLP) l’interesse per il linguaggio figurativo è particolarmente aumentato negli ultimi anni, grazie alla quantità d’informazione linguistica messa a disposizione dal web e dai social network. Il linguaggio figurati...

Research paper thumbnail of Exploration of Misogyny in Spanish and English Tweets

Nowadays, misogynistic abuse online has become a serious issue due, especially, to anonymity and ... more Nowadays, misogynistic abuse online has become a serious issue due, especially, to anonymity and interactivity of the web that facilitate the increase and the permanence of the offensive comments on the web. In this paper, we present an approach based on stylistic and specific topic information for the detection of misogyny, exploring the several aspects of misogynistic Spanish and English user generated texts on Twitter. Our method has been evaluated in the framework of our participation in the AMI shared task at IberEval 2018 obtaining promising results.

Research paper thumbnail of The role of sarcasm in hate speech.A multilingual perspective

The importance of the detection of aggressiveness in social media is due to real effects of viole... more The importance of the detection of aggressiveness in social media is due to real effects of violence provoked by negative behavior online. For this reason, hate speech online is a real problem in modern society and the necessity of control of usergenerated contents has become one of the priorities for governments, social media platforms and Internet companies. Current methodologies are far from solving this problem. Indeed, several aggressive comments are also disguised as sarcastic. In this perspective, this research proposal wants to investigate the role played by creative linguistic devices, especially sarcasm, in hate speech in multilingual context.

Research paper thumbnail of Deep Analysis in Aggressive Mexican Tweets

The importance of the detection of aggressiveness in social media is due to real effects of viole... more The importance of the detection of aggressiveness in social media is due to real effects of violence provoked by negative behavior online. Indeed, this kind of legal cases are increasing in the last years. For this reason, the necessity of controlling user-generated contents has become one of the priorities for many Internet companies, although current methodologies are far from solving this problem. Therefore, in this work we propose an innovative approach that combines deep learning framework with linguistic features specific for this issue. This approach has been evaluated and compared with other ones in the framework of the MEX-A3T shared task at IberEval on aggressiveness analysis in Spanish Mexican tweets. In spite of our novel approach, we obtained low results.

Research paper thumbnail of Computational Models for Irony Detection in Three Spanish Variants

The lack of understanding of figurative language online, such as ironic messages, is a common cau... more The lack of understanding of figurative language online, such as ironic messages, is a common cause of error for systems that analyze automatically the users’ opinions online detecting sentiment, emotions or stance. In order to deal with this problem of automatic processing of natural language, IroSvA shared task at IberLef 2019 asks participants to detect, for the first time, irony in short texts written in Spanish language, considering the three linguistic variants from Spain, Mexico and Cuba. Another novelty of this task is the presence of labels specifying the context of the utterance, such as current political or social issues discussed online. In the context of this shared task, we approached irony detection in Spanish short texts trying to exploit the provided topic information. In addition, we investigated the usefulness of stylistic, lexical and affective features during the development of the irony detection models for the three Spanish variants. Experimental results and f...

Research paper thumbnail of The unbearable hurtfulness of sarcasm

Expert Systems with Applications

Research paper thumbnail of Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter

Journal of Intelligent & Fuzzy Systems