{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/representation-mapping-a-novel-approach-to","title":"Representation Mapping: A Novel Approach to Generate High-Quality Multi-Lingual Emotion Lexicons","arxiv_id":"1807.00775","date":"2018-07-02","proceeding":"LREC 2018 5","authors":["Sven Buechel","Udo Hahn"],"abstract":"In the past years, sentiment analysis has increasingly shifted attention to\nrepresentational frameworks more expressive than semantic polarity (being\npositive, negative or neutral). However, these richer formats (like Basic\nEmotions or Valence-Arousal-Dominance, and variants therefrom), rooted in\npsychological research, tend to proliferate the number of representation\nschemes for emotion encoding. Thus, a large amount of representationally\nincompatible emotion lexicons has been developed by various research groups\nadopting one or the other emotion representation format. As a consequence, the\nreusability of these resources decreases as does the comparability of systems\nusing them. In this paper, we propose to solve this dilemma by methods and\ntools which map different representation formats onto each other for the sake\nof mutual compatibility and interoperability of language resources. We present\nthe first large-scale investigation of such representation mappings for four\ntypologically diverse languages and find evidence that our approach produces\n(near-)gold quality emotion lexicons, even in cross-lingual settings. Finally,\nwe use our models to create new lexicons for eight typologically diverse\nlanguages.","url_abs":"http://arxiv.org/abs/1807.00775v1","url_pdf":"http://arxiv.org/pdf/1807.00775v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"representation-mapping-a-novel-approach-to","repo_url":"https://github.com/JULIELab/EmoMap","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}