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Learning Activities in Colours and Rainbows for Programming Skill Development ...
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Regionalized models for Spanish language variations based on Twitter ...
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Analyzing a Carceral Algorithm used by the Pennsylvania Department of Corrections ...
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OkwuGbé: End-to-End Speech Recognition for Fon and Igbo ...
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When the Echo Chamber Shatters: Examining the Use of Community-Specific Language Post-Subreddit Ban ...
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GENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena ...
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Natural-Language Multi-Agent Simulations of Argumentative Opinion Dynamics ...
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Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Do ...
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Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI ...
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53 |
Efficiency of Using Utility for Usernames Verification in Online Community Management ...
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54 |
Political Ideology and Polarization of Policy Positions: A Multi-dimensional Approach ...
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55 |
BIOPAK Flasher: Epidemic disease monitoring and detection in Pakistan using text mining ...
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56 |
Towards Knowledge-Grounded Counter Narrative Generation for Hate Speech ...
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57 |
Theoretical foundations and limits of word embeddings: what types of meaning can they capture? ...
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58 |
Modeling Framing in Immigration Discourse on Social Media ...
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60 |
Exploring Polarization of Users Behavior on Twitter During the 2019 South American Protests ...
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Abstract:
Research across different disciplines has documented the expanding polarization in social media. However, much of it focused on the US political system or its culturally controversial topics. In this work, we explore polarization on Twitter in a different context, namely the protest that paralyzed several countries in the South American region in 2019. By leveraging users' endorsement of politicians' tweets and hashtag campaigns with defined stances towards the protest (for or against), we construct a weakly labeled stance dataset with millions of users. We explore polarization in two related dimensions: language and news consumption patterns. In terms of linguistic polarization, we apply recent insights that leveraged machine translation methods, showing that the two communities speak consistently "different" languages, mainly along ideological lines (e.g., fascist translates to communist). Our results indicate that this recently-proposed methodology is also informative in different languages and contexts ...
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Keyword:
Computers and Society cs.CY; FOS Computer and information sciences; Social and Information Networks cs.SI
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URL: https://dx.doi.org/10.48550/arxiv.2104.05611 https://arxiv.org/abs/2104.05611
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