Computational rule-based model for Irony Detection in Italian Tweets

Frenda, Simona

doi:10.4000/books.aaccademia.2015

Cited by 8 publications

(9 citation statements)

References 5 publications

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“…As for future work, we plan to propose alternative large-scale methods to collect implicit and subtle messages by targeting "hateful" users, manual creation (Wiegand et al, 2021a(Wiegand et al, , 2022 or refining human-in-the-loop generative methods as in (Hartvigsen et al, 2022). Also, we will investigate features modeling implicit properties (Wallace et al, 2014;Troiano et al, 2018;Frenda and Patti, 2019) and new model architectures for HS detection (Nejadgholi et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

An In-depth Analysis of Implicit and Subtle Hate Speech Messages

Ocampo,

Sviridova,

Cabrio

et al. 2023

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

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The research carried out so far in detecting abusive content in social media has primarily focused on overt forms of hate speech. While explicit hate speech (HS) is more easily identifiable by recognizing hateful words, messages containing linguistically subtle and implicit forms of HS (as circumlocution, metaphors and sarcasm) constitute a real challenge for automatic systems. While the sneaky and tricky nature of subtle messages might be perceived as less hurtful with respect to the same content expressed clearly, such abuse is at least as harmful as overt abuse. In this paper, we first provide an in-depth and systematic analysis of 7 standard benchmarks for HS detection, relying on a fine-grained and linguistically-grounded definition of implicit and subtle messages. Then, we experiment with state-of-the-art neural network architectures on two supervised tasks, namely implicit HS and subtle HS message classification. We show that while such models perform satisfactory on explicit messages, they fail to detect implicit and subtle content, highlighting the fact that HS detection is not a solved problem and deserves further investigation.

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Section: Discussionmentioning

confidence: 99%

An In-depth Analysis of Implicit and Subtle Hate Speech Messages

Ocampo,

Sviridova,

Cabrio

et al. 2023

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

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“…Detecting whether a text is ironic constitutes a challenging semantic task known as irony detection. Being able to detect irony requires a deep comprehension of the text and is notably subjective, as individuals with varying cultural backgrounds may interpret the irony differently (Frenda et al, 2023). This task is usually framed as a binary classification problem, where the goal is to predict whether a text is ironic or not.…”

Section: Tasksmentioning

confidence: 99%

pysentimiento: A Python Toolkit for Opinion Mining and Social NLP tasks

Perez,

Rajngewerc,

Giudici

et al. 2023

Preprint

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In recent years, the extraction of opinions and information from user-generated text has attracted a lot of interest, largely due to the unprecedented volume of content in Social Media. However, social researchers face some issues in adopting cutting-edge tools for these tasks, as they are usually behind commercial APIs, unavailable for other languages than English, or very complex to use for non-experts. To address these issues, we present pysentimiento, a comprehensive multilingual Python toolkit designed for opinion mining and other Social NLP tasks. This open-source library brings state-of-the-art models for Spanish, English, Italian, and Portuguese in an easy-to-use Python library, allowing researchers to leverage these techniques. We present a comprehensive assessment of performance for several pre-trained language models across a variety of tasks, languages, and datasets, including an evaluation of fairness in the results.

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“…The data sets generated during this study are not publicly available due to the Twitter's terms of use under the European General Data Protection Regulation, tweets cannot be shared [21]. In addition, the full codes used to create the neural network are available on GitHub [41].…”

Section: Data Availabilitymentioning

confidence: 99%

Fight Against the Mandatory COVID-19 Immunity Passport on Twitter: Natural Language Processing Study

Gable,

Sauvayre,

Chauvière

2023

J Med Internet Res

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Background To contain and curb the spread of COVID-19, the governments of countries around the world have used different strategies (lockdown, mandatory vaccination, immunity passports, voluntary social distancing, etc). Objective This study aims to examine the reactions produced by the public announcement of a binding political decision presented by the president of the French Republic, Emmanuel Macron, on July 12, 2021, which imposed vaccination on caregivers and an immunity passport on all French people to access restaurants, cinemas, bars, and so forth. Methods To measure these announcement reactions, 901,908 unique tweets posted on Twitter (Twitter Inc) between July 12 and August 11, 2021, were extracted. A neural network was constructed to examine the arguments of the tweets and to identify the types of arguments used by Twitter users. Results This study shows that in the debate about mandatory vaccination and immunity passports, mostly “con” arguments (399,803/847,725, 47%; χ26=952.8; P<.001) and “scientific” arguments (317,156/803,583, 39%; χ26=5006.8; P<.001) were used. Conclusions This study shows that during July and August 2021, social events permeating the public sphere and discussions about mandatory vaccination and immunity passports collided on Twitter. Moreover, a political decision based on scientific arguments led citizens to challenge it using pseudoscientific arguments contesting the effectiveness of vaccination and the validity of these political decisions.

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Computational rule-based model for Irony Detection in Italian Tweets

Cited by 8 publications

References 5 publications

An In-depth Analysis of Implicit and Subtle Hate Speech Messages

An In-depth Analysis of Implicit and Subtle Hate Speech Messages

pysentimiento: A Python Toolkit for Opinion Mining and Social NLP tasks

Fight Against the Mandatory COVID-19 Immunity Passport on Twitter: Natural Language Processing Study

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