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Conversational Psychology Emotion Dataset
Data Science and Analytics
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Free
About
This dataset provides psychological conversations between two individuals, complete with preceding context. Its primary aim is to facilitate the inference of underlying emotions within each utterance. It is ideal for gaining insights into the complex relationships between emotions and textual conversations. This data can be used to develop automatic dialogue systems that recognise feelings and emotions, build sentiment analysis tools, or train machine learning models to predict emotions in conversational exchanges.
Columns
- text: The actual text of the conversation occurring between the two people. This is a string data type.
- label: The specific emotion linked to each turn of dialogue. Possible values include Happy, Sad, Angry, or Others. This is also a string data type.
Distribution
The dataset is structured into three separate CSV files:
train.csv, test.csv, and validation.csv. Each file contains text and associated labels for psychological conversations. The exact total number of rows or records across all files is not specified, however, the test.csv file includes unique values for labels and their counts.Usage
This dataset is well-suited for a variety of applications, including:
- Developing automatic dialogue systems capable of recognising and understanding emotions expressed in conversations.
- Building sentiment analysis tools designed to extract emotions from textual dialogues.
- Training machine learning models, such as deep Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), or Long Short-Term Memory (LSTMs) networks, to accurately predict the emotion of each utterance.
- Exploring and gaining deeper insights into the intricate connections between human emotions and conversational text.
Coverage
The dataset's geographic scope is global. Specific information regarding time range or demographic details for the conversational data is not provided.
License
CC0
Who Can Use It
This dataset is particularly useful for:
- Data Scientists and Machine Learning Engineers aiming to build or improve emotion recognition models.
- Researchers in natural language processing (NLP), computational linguistics, and artificial intelligence focusing on sentiment analysis and dialogue understanding.
- Developers creating AI-powered conversational agents or emotionally intelligent systems.
Dataset Name Suggestions
- Emotion Recognition in Conversations
- Conversational Psychology Emotion Dataset
- Textual Emotion Inference Data
- Dialogue Emotion Analysis Dataset
Attributes
Original Data Source: Emo (Infer Underlying Emotion)
QUALITY