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Cross-Lingual Classification of Political Texts Using Multilingual Sentence Embeddings

https://doi.org/10.1017/pan.2022.29

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What this work says

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Cross-Domain Topic Classification for Political Texts

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Extracting Policy Positions from Political Texts Using Words as Data

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Crowd-sourced Text Analysis: Reproducible and Agile Production of Political Data

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The Ties That Bind: Text Similarities and Conditional Diffusion among Parties

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Word embeddings quantify 100 years of gender and ethnic stereotypes

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More than Bags of Words: Sentiment Analysis with Word Embeddings

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Overcoming Language Barriers: Assessing the Potential of Machine Translation and Topic Modeling for the Comparative Analysis of Multilingual Text Corpora

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Reproducible Extraction of Cross-lingual Topics (rectr)

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Machine Translation Vs. Multilingual Dictionaries Assessing Two Strategies for the Topic Modeling of Multilingual Text Collections

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Building the Bridge: Topic Modeling for Comparative Research

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Three Gaps in Computational Text Analysis Methods for Social Sciences: A Research Agenda

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Computer-Assisted Topic Classification for Mixed-Methods Social Science Research

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Automatic translation, context, and supervised learning in comparative politics

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Word Embeddings: What Works, What Doesn’t, and How to Tell the Difference for Applied Research

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Coder Reliability and Misclassification in the Human Coding of Party Manifestos

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Positions and saliency of immigration in party manifestos: A novel dataset using crowd coding

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How to Analyze Political Attention with Minimal Assumptions and Costs

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Multilingual Sentiment Analysis: A New Approach to Measuring Conflict in Legislative Speeches

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Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

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Using Supervised Machine Learning to Code Policy Issues

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Estimating party positions on immigration: Assessing the reliability and validity of different methods

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Automated content analysis across six languages

inferredcites →https://doi.org/10.18653/v1/2020.acl-demos.12openalex-snapshot

Multilingual Universal Sentence Encoder for Semantic Retrieval

inferredcites →https://doi.org/10.18653/v1/2020.acl-main.747openalex-snapshot

Unsupervised Cross-lingual Representation Learning at Scale

inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.365openalex-snapshot

Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation

inferredcites →https://doi.org/10.18653/v1/n19-5004openalex-snapshot

Transfer Learning in Natural Language Processing

inferredcites →https://doi.org/10.18653/v1/w17-2906openalex-snapshot

Cross-Lingual Classification of Topics in Political Texts

inferredcites →https://doi.org/10.24433/co.5199179.v1openalex-snapshot

Cross-lingual classification of political texts using multilingual sentence embeddings

inferredcites →https://doi.org/10.25522/manifesto.mpds.2020aopenalex-snapshot

Manifesto Project Dataset

inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot

Glove: Global Vectors for Word Representation

inferredcites →https://doi.org/10.48550/arxiv.2010.11125openalex-snapshot

Beyond English-Centric Multilingual Machine Translation

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Greasing the wheels for comparative communication research: Supervised text classification for multilingual corpora

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Replication Data for: Cross-lingual classification of political texts using multilingual sentence embeddings

What points at this work

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