Papers by Annerose Eichel

3 papers
Made of Steel? Learning Plausible Materials for Components in the Vehicle Repair Domain (2023.eacl-main)

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Challenge: a novel approach to learn domain-specific plausible materials for components in the vehicle repair domain is proposed . connecting a symptom to an underlying cause is a crucial building block for natural language understanding across domains.
Approach: They propose a method to aggregate salient predictions from a set of cloze task style templates and use a Wikipedia corpus to augment the model.
Outcome: The proposed approach outperforms a traditional pattern-based approach by exploiting the compositionality assumption in a cloze task style setting.
Investigating Independence vs. Control: Agenda-Setting in Russian News Coverage on Social Media (2022.lrec-1)

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Challenge: a major challenge in the media industry has always been its targeted manipulation, says a new study . agenda-setting is a well-known phenomenon in political science . authors explore the relationship between economic indicators and mentions of foreign geopolitical entities .
Approach: They investigate agenda-setting in the Russian social media landscape . they explore the relation between economic indicators and mentions of foreign geopolitical entities .
Outcome: The authors examine the relationship between economic indicators and mentions of foreign geopolitical entities, as well as of Russia itself.
Willkommens-Merkel, Chaos-Johnson, and Tore-Klose: Modeling the Evaluative Meaning of German Personal Name Compounds (2024.lrec-main)

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Challenge: Personal name compounds (PNCs) are compositions that refer to a person, such as Willkommens-Merkel ('Welcome-Meerkel') and a personal name such as Merkel.
Approach: They propose to model 321 personal name compounds and their corresponding full names at discourse level and compare two approaches to assess whether a PNC is more positively or negatively evaluative . they further enrich data with personal, domain-specific, and extra-linguistic information and perform regression analyses revealing that factors including compound and modifier valence, domain, and political party membership influence how a pnc is evaluated.
Outcome: The proposed model shows that the PNCs are perceived as more positively or negatively than their full name and that they are perceived to be more positive or negative.

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