Negotiation metaphor translation

This dataset, titled "Negotiation Metaphor Translation," was created as part of a research project investigating the dynamics of metaphor translation in negotiation contexts. The data was generated through a combination of controlled translation tasks, longitudinal studies, and domain-specific analyses, involving both human translators and computational models.Data Generation and ProcessingThe dataset was compiled from multiple sources:Controlled translation tasks were designed and administered to professional translators, focusing on negotiation-related metaphors in Chinese and English.Longitudinal study data was collected over several translation sessions to capture changes in translation strategies and outcomes over time.Domain-specific analysis involved expert annotation and categorization of metaphors and negotiation strategies.Performance metrics were computed using both manual evaluation and automated scoring methods.All data was anonymized to protect participant privacy. Data processing included normalization of text, removal of personally identifiable information, and standardization of file formats.Temporal and Geographical ScopeThe data was collected between 2022 and 2024, primarily involving participants from Taiwan (Province of China) and English-speaking countries. The temporal resolution varies by file, with some files representing single translation sessions and others aggregating data over multiple sessions.Data Structure and File DescriptionsThe dataset is organized as follows:performance_metrics_summary.csv: Contains summary statistics of translation performance, including accuracy, fluency, and adequacy scores. Columns include Task_ID, Translator_ID, Accuracy, Fluency, Adequacy, and Comments.domain_specific_analysis.csv: Provides detailed analysis of metaphors and negotiation strategies by domain. Columns include Domain, Metaphor_Type, Strategy, Frequency, and Notes.negotiation_dynamics.csv: Records the dynamics of negotiation during translation, such as turn-taking, conflict resolution, and schema adaptation. Columns include Session_ID, Turn_Number, Speaker, Action, and Outcome.longitudinal_study_data.csv: Tracks changes in translation strategies and outcomes over time. Columns include Participant_ID, Session_Date, Strategy_Used, Outcome, and Comments.conflict_resolution_strategies.csv: Lists various strategies used to resolve conflicts in metaphor translation. Columns include Strategy_ID, Description, Effectiveness_Rating, and Example.All files are in CSV format and can be opened with standard spreadsheet software such as Microsoft Excel or LibreOffice Calc.Data SizeEach CSV file ranges from approximately 10 KB to 200 KB, depending on the number of entries.Column Names and UnitsEach file contains a header row with descriptive column names. Units of measurement, where applicable, are indicated in the column names or described in the accompanying README file.Missing DataSome entries may contain missing values, indicated by empty cells. These typically occur when a particular metric or annotation was not applicable or could not be determined for a given instance.Data Quality and Error ReportingData was manually checked for consistency and accuracy. Any known errors or limitations are documented in the README.md file included in the dataset.File Formats and SoftwareAll data files are provided in standard CSV format, compatible with most data analysis and spreadsheet tools. No proprietary or rare file formats are used.├── 📊 experimental_results/│ ├── performance_metrics_summary.csv  │ ├── domain_specific_analysis.csv│ ├── negotiation_dynamics.csv│ ├── longitudinal_study_data.csv│ ├── conflict_resolution_strategies.csv| └──Readme.md