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Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study ...
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Towards Knowledge-Grounded Counter Narrative Generation for Hate Speech ...
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Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech ...
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Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement ...
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Towards Knowledge-Grounded Counter Narrative Generation for Hate Speech ...
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Regrexit or not Regrexit: Aspect-based Sentiment Analysis in Polarized Contexts
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In: COLING'2020 - 28th International Conference on Computational Linguistics (COLING'2020) ; https://hal.inria.fr/hal-03031812 ; COLING'2020 - 28th International Conference on Computational Linguistics (COLING'2020), Dec 2020, Barcelona / Online, Spain (2020)
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DepecheMood++: a Bilingual Emotion Lexicon Built Through Simple Yet Powerful Techniques ...
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A Generative-Discriminative Framework for Title Generation in the E-commerce Domain
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Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines ...
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Deep Feelings: A Massive Cross-Lingual Study on the Relation between Emotions and Virality ...
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Echoes of Persuasion: The Effect of Euphony in Persuasive Communication ...
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SentiWords: Deriving a High Precision and High Coverage Lexicon for Sentiment Analysis ...
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DepecheMood: a Lexicon for Emotion Analysis from Crowd-Annotated News ...
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Do Linguistic Style and Readability of Scientific Abstracts Affect their Virality?
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In: Proceedings of the International AAAI Conference on Web and Social Media; Vol. 6 No. 1 (2012): Sixth International AAAI Conference on Weblogs and Social Media ; 2334-0770 ; 2162-3449 (2012)
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Do Linguistic Style and Readability of Scientific Abstracts affect their Virality? ...
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Abstract:
Reactions to textual content posted in an online social network show different dynamics depending on the linguistic style and readability of the submitted content. Do similar dynamics exist for responses to scientific articles? Our intuition, supported by previous research, suggests that the success of a scientific article depends on its content, rather than on its linguistic style. In this article, we examine a corpus of scientific abstracts and three forms of associated reactions: article downloads, citations, and bookmarks. Through a class-based psycholinguistic analysis and readability indices tests, we show that certain stylistic and readability features of abstracts clearly concur in determining the success and viral capability of a scientific article. ... : Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media (ICWSM 2012), 4-8 June 2012, Dublin, Ireland ...
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Keyword:
Computation and Language cs.CL; Digital Libraries cs.DL; FOS Computer and information sciences; Social and Information Networks cs.SI
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URL: https://dx.doi.org/10.48550/arxiv.1203.4238 https://arxiv.org/abs/1203.4238
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