#andràtuttobene: Images, Texts, Emojis and Geodata in a Sentiment Analysis Pipeline

Vitale, Pierluigi; Pelosi, Serena; Falco, Mariacristina

doi:10.4000/books.aaccademia.8954

Cited by 14 publications

(4 citation statements)

References 30 publications

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“…This comes from the exploitation of an Italian sentiment lexicon, SentIta 5 [3] combined with the use of Finite-State Transducers for the syntactic analysis and the pattern annotation. SentIta includes more than 20,000 entries, enriched through taboo words [35] , idioms [36] , hashtag and emojis [37] .…”

Section: Methodsmentioning

confidence: 99%

Lexicon-based sentiment analysis to detect opinions and attitude towards COVID-19 vaccines on Twitter in Italy

Catelli

Pelosi

Comito

et al. 2023

Computers in Biology and Medicine

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Section: Methodsmentioning

confidence: 99%

Lexicon-based sentiment analysis to detect opinions and attitude towards COVID-19 vaccines on Twitter in Italy

Catelli

Pelosi

Comito

et al. 2023

Computers in Biology and Medicine

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“…Afterwards, morphological finite state automata (FSA) have been used to semi-automatically extend the annotation over verbs, nouns and adverbs [65]. The result is a set of dictionaries of more than 20,000 entries, which has recently been enriched by taboo words [66], idioms [67] and emojis [68]. The lexicon of the FICLIT+CS@UniBO System, which has been created for the EVALITA 2014 SENTIPOLC task, includes adjectives and adverbs from the De Mauro-Paravia Italian dictionary and nouns and verbs from the Sentix database.…”

Section: Lexicon-based Approachesmentioning

confidence: 99%

Lexicon-Based vs. Bert-Based Sentiment Analysis: A Comparative Study in Italian

2022

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Recent evolutions in the e-commerce market have led to an increasing importance attributed by consumers to product reviews made by third parties before proceeding to purchase. The industry, in order to improve the offer intercepting the discontent of consumers, has placed increasing attention towards systems able to identify the sentiment expressed by buyers, whether positive or negative. From a technological point of view, the literature in recent years has seen the development of two types of methodologies: those based on lexicons and those based on machine and deep learning techniques. This study proposes a comparison between these technologies in the Italian market, one of the largest in the world, exploiting an ad hoc dataset: scientific evidence generally shows the superiority of language models such as BERT built on deep neural networks, but it opens several considerations on the effectiveness and improvement of these solutions when compared to those based on lexicons in the presence of datasets of reduced size such as the one under study, a common condition for languages other than English or Chinese.

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“…These data are considered relevant as they allow us to generalize about human social and linguistic behavior, especially regarding the pandemic event. Among the tasks that have been conducted on data drawn from social media in this period, sentiment analysis, emotion profiling and topic modeling are the most common (Gagliardi et al, 2020;Vitale et al, 2020;Stella et al, 2020a;Stella et al, 2020b;Stella et al, 2021;De Santis et al, 2020;Sciandra, 2020;Trevisan et al, 2021;Gozzi et al, 2020;Kruspe et al, 2020;Hussain et al, 2021;Chakraborty et al, 2020;Nemes e Kiss, 2020;Jelodar et al, 2021;Lamsal, 2020;Duong et al, 2021;Gupta et al, 2021;Sullivan et al, 2021;Su et al, 2020;Garcia et Berton, 2021;Ahmed et al, 2020).…”

Section: State Of the Artmentioning

confidence: 99%

Introducing a Gold Standard Corpus from Young Multilinguals for the Evaluation of Automatic UD-PoS Taggers for Italian

Schmalz¹,

Frey²,

Stemle³

2022

Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021

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The eighth edition of the Italian Conference on Computational Linguistics (CLiC-it 2021) was held at Università degli Studi di Milano-Bicocca from 26th to 28th January 2022.After the edition of 2020, which was held in fully virtual mode due to the health emergency related to Covid-19, CLiC-it 2021 represented the first moment for the Italian research community of Computational Linguistics to meet in person after more than one year of full/partial lockdown. Although the conference was held in dual mode, we strongly suggested the participants to attend it coming to Milan. Indeed, we received a strong feedback on this aspect from the community, which was eager to meet in person and enjoy both the scientific and social events together with the colleagues. In total, 99 participants registered to the conference benefiting from the early registration fee, 91 out of which expressed their intention to attend the event in person, which we consider as a very positive indication of enthusiasm from the community, given the uncertain situation due to the evolution of the pandemic in Italy.In total, we received 68 proposals, organized in the following specific tracks: Information Extraction,

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#andràtuttobene: Images, Texts, Emojis and Geodata in a Sentiment Analysis Pipeline

Cited by 14 publications

References 30 publications

Lexicon-based sentiment analysis to detect opinions and attitude towards COVID-19 vaccines on Twitter in Italy

Lexicon-based sentiment analysis to detect opinions and attitude towards COVID-19 vaccines on Twitter in Italy

Lexicon-Based vs. Bert-Based Sentiment Analysis: A Comparative Study in Italian

Introducing a Gold Standard Corpus from Young Multilinguals for the Evaluation of Automatic UD-PoS Taggers for Italian

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