SubjectivITA: An Italian Corpus for Subjectivity Detection in Newspapers

Antici, Francesco; Bolognini, Luca; Inajetovic, Matteo Antonio; Ivasiuk, Bogdan; Galassi, Andrea; Ruggeri, Federico

doi:10.1007/978-3-030-85251-1_4

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…). These results seem to confirm previous findings, regarding the importance of subjectivity analysis [83] for the task of argument mining [84]. For what concerns link prediction, among the top-ranked tokens some discourse markers can be observed (e.g., "depending", "owing", "whenever", "firstly", "second", "while", "even"), as well as verbs in present continuous form, but also words that do not seem correlated with the task, such as "spam" or "phased".…”

Section: Evidencessupporting

confidence: 92%

Multi-Task Attentive Residual Networks for Argument Mining

Galassi

Lippi

Torroni

2023

IEEE/ACM Trans. Audio Speech Lang. Process.

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We explore the use of residual networks and neural attention for multiple argument mining tasks. We propose a residual architecture that exploits attention, multi-task learning, and makes use of ensemble, without any assumption on document or argument structure. We present an extensive experimental evaluation on five different corpora of user-generated comments, scientific publications, and persuasive essays. Our results show that our approach is a strong competitor against state-of-the-art architectures with a higher computational footprint or corpus-specific design, representing an interesting compromise between generality, performance accuracy and reduced model size.

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Section: Evidencessupporting

confidence: 92%