synthetic_dataset.csv
<p dir="ltr"><b>Title</b>: Privacy-Enhanced Sentiment Analysis Dataset for Mental Health Research</p><p dir="ltr"><b>Description</b>:<br>This dataset has been compiled to support the study titled <i>"Privacy-Enhanced Sent...
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2024
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| Summary: | <p dir="ltr"><b>Title</b>: Privacy-Enhanced Sentiment Analysis Dataset for Mental Health Research</p><p dir="ltr"><b>Description</b>:<br>This dataset has been compiled to support the study titled <i>"Privacy-Enhanced Sentiment Analysis in Mental Health: Federated Learning with Data Obfuscation and BERT"</i>. It contains anonymized text samples labeled with sentiment categories relevant to mental health analysis. The dataset was generated with data obfuscation techniques to protect participant privacy while preserving the key patterns needed for sentiment analysis in mental health contexts.</p><p dir="ltr"><b>Contents</b>:</p><ul><li><b>Text Samples</b>: Anonymized text data categorized by sentiment, designed to reflect common emotional responses pertinent to mental health assessments.</li><li><b>Sentiment Labels</b>: Labels including emotions such as happiness, sadness, anxiety, and calmness, are suitable for training and evaluating sentiment analysis models.</li></ul><p dir="ltr"><b>Usage</b>:<br>This dataset is intended for research purposes, especially for training machine learning models in sentiment analysis and mental health studies under privacy constraints.</p> |
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