2026-10-14T18:53:52Z https://www.scidb.cn/oai

10.57760/sciencedb.38271 2026-06-01T15:07:46Z

2026-06-01 Adaptive Text Generation with Personality Types and Continuous Emotion Intensity Dataset doi:10.57760/sciencedb.38271 en This dataset is released as part of the study:Adaptive Text Generation with Personality Types and Continuous Emotion IntensityIt contains a Chinese controllable text generation dataset integrating MBTI personality types and continuous emotion intensity annotations, designed for research in affective natural language generation. Dataset OverviewTo ensure consistency and usability, the generated texts are constrained to a length of 10–50 Chinese characters. For each MBTI personality type, 15,000 samples are generated, resulting in a balanced dataset across all 16 personality categories. Each sample is further annotated with a six-dimensional emotion intensity vector using an external emotion annotation model.formatted_style_data.csv (240000 samples) File FormatEach row contains the following fields:text,angry,fear,happy,neutral,sad,surprise,type,ME,target_text Task DefinitionThis dataset supports the task of:Controllable Text Generation conditioned on Personality Type and Continuous Emotion IntensityThe model must generate fluent and coherent text that:Aligns with the specified MBTI personality typeReflects the given multi-dimensional emotion intensity distributionPreserves semantic consistency with the original text Emotion RepresentationEmotion is represented as a continuous probability-like distribution over six basic emotions:Emotion Descriptionangry anger intensityfear fear intensityhappy happiness intensityneutral neutralitysad sadnesssurprise surprise intensityThe sum of values is not constrained to 1, reflecting multi-label emotional expression. Personality RepresentationPersonality types follow the MBTI framework, including 16 categories:ISTJ, ISFJ, INFJ, INTJISTP, ISFP, INFP, INTPESTP, ESFP, ENFP, ENTPESTJ, ESFJ, ENFJ, ENTJ⚙️ Potential ApplicationsThis dataset can be used for:Personality-conditioned text generationEmotion-aware language modelingControllable natural language generation (NLG)Affective computing researchHuman-computer interaction systems CitationIf you use this dataset, please cite:@article{adaptive_personality_emotion_2026, title={Adaptive Text Generation with Personality Types and Continuous Emotion Intensity}, author={Jingyi Zhou. Senlin Luo, Haofan Chen}, Affective text generation; Controllable text generation; Personality-aware language modeling; Emotion intensity modeling; Adaptive decoding; Chinese natural language generation Jingyi Zhou PUBLIC https://creativecommons.org/licenses/by-nc-sa/4.0/ dataset Science Data Bank