Issue Framing in Online Discussion Fora

Hartmann, Mareike; Jansen, Tallulah; Augenstein, Isabelle; Søgaard, Anders

doi:10.18653/v1/n19-1142

Cited by 21 publications

(18 citation statements)

References 28 publications

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“…This study is based on the distribution of animated news videos to a selected viewership group and a survey of the viewers to determine reactions to the materials viewed. It was known that the links between attitudes and perceptions shaped by media framing and the consequent political behavior of individuals (Hartmann et al, 2019) are enhanced by the qualitative character of news frames and presentation variables (Bracken, 2006). Frames that portray social protest as a noble cause, for example, result in larger protest waves (Cooper, 2002).…”

Section: Study Objects and Methodologymentioning

confidence: 99%

The Impact of “Manipulated News” on Student Attitudes and Perceptions and Their Participation in the Umbrella Movement in Hong Kong

Wong¹,

Zhu

Krever

et al. 2021

Social Media + Society

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While the impact of fake news on viewers, particularly marginalized media users, has been a cause of growing concern, there has been little attention paid to the phenomenon of deliberately “manipulated” news published on social media by mainstream news publishers. Using qualitative content analysis and quantitative survey research, this study showed that consciously biased animated news videos released in the midst of the Umbrella Movement protests in Hong Kong impacted on both the attitudes of students and their participation in the protests. The findings raise concerns over potential use of the format by media owners to promote their preferred ideologies.

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Section: Study Objects and Methodologymentioning

confidence: 99%

The Impact of “Manipulated News” on Student Attitudes and Perceptions and Their Participation in the Umbrella Movement in Hong Kong

Wong¹,

Zhu

Krever

et al. 2021

Social Media + Society

View full text Add to dashboard Cite

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“…Yet, their method does not allow to detect frames. Other works present methods to automatically label sentences of news articles and online discussions with frames (Hartmann et al, 2019;Naderi and Hirst, 2017). These methods are, however, limited to a small set of predefined frames that represent high-level concepts.…”

Section: Related Workmentioning

confidence: 99%

Aspect-Controlled Neural Argument Generation

Schiller¹,

Daxenberger²,

Gurevych³

2021

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

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We rely on arguments in our daily lives to deliver our opinions and base them on evidence, making them more convincing in turn. However, finding and formulating arguments can be challenging. In this work, we present the Arg-CTRL-a language model for argument generation that can be controlled to generate sentence-level arguments for a given topic, stance, and aspect. We define argument aspect detection as a necessary method to allow this fine-granular control and crowdsource a dataset with 5,032 arguments annotated with aspects. Our evaluation shows that the Arg-CTRL is able to generate high-quality, aspectspecific arguments, applicable to automatic counter-argument generation. We publish the model weights and all datasets and code to train the Arg-CTRL. 1 Nuclear reactors produce radioactive waste ...

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“…Huguet Cabot et al (2020) addressed this task by leveraging emotion and metaphor detection in an MTL setup. Other works have also explored sentence-level framing (Johnson et al, 2017;Hartmann et al, 2019).…”

Section: Modelling Political Discourse In Nlpmentioning

confidence: 99%

Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions

Huguet-Cabot¹,

Abadi²,

Fischer³

et al. 2021

Preprint

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Computational modelling of political discourse tasks has become an increasingly important area of research in natural language processing. Populist rhetoric has risen across the political sphere in recent years; however, computational approaches to it have been scarce due to its complex nature. In this paper, we present the new Us vs. Them dataset, consisting of 6861 Reddit comments annotated for populist attitudes and the first large-scale computational models of this phenomenon. We investigate the relationship between populist mindsets and social groups, as well as a range of emotions typically associated with these. We set a baseline for two tasks related to populist attitudes and present a set of multi-task learning models that leverage and demonstrate the importance of emotion and group identification as auxiliary tasks.

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Issue Framing in Online Discussion Fora

Cited by 21 publications

References 28 publications

The Impact of “Manipulated News” on Student Attitudes and Perceptions and Their Participation in the Umbrella Movement in Hong Kong

The Impact of “Manipulated News” on Student Attitudes and Perceptions and Their Participation in the Umbrella Movement in Hong Kong

Aspect-Controlled Neural Argument Generation

Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions

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